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{ "count": 30374, "next": "?page=2", "previous": null, "list": [ { "name": "OptimJV3", "description": "Optimize parameters of JARVIS3 - a genomic compressor - for compression of genomic sequences", "homepage": "https://github.com/cobilab/OptimJV3", "biotoolsID": "optimjv3", "biotoolsCURIE": "biotools:optimjv3", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "ritaferrolho", "additionDate": "2025-04-03T15:58:10.986044Z", "lastUpdate": "2025-04-03T15:58:10.988726Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "neXtProt", "description": "neXtProt was an innovative knowledge platform dedicated to human proteins. This resource contained a wealth of high-quality data on all the human proteins that are produced by the 20'000 protein-coding genes found in the human genome. The content of neXtProt was continuously extended so as to provide many more carefully selected data sets and analysis tools. neXtProt data and tools have been archived.", "homepage": "https://www.expasy.org/archives/nextprot", "biotoolsID": "nextprot", "biotoolsCURIE": "biotools:nextprot", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2479", "term": "Protein sequence analysis" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" }, { "uri": "http://edamontology.org/operation_2406", "term": "Protein structure analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_0601", "term": "Protein modifications" }, { "uri": "http://edamontology.org/topic_3120", "term": "Protein variants" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "CC-BY-4.0", "collectionID": [ "Rare Disease", "Proteomics" ], "maturity": "Legacy", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [ "Data" ], "elixirNode": [ "Switzerland" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/calipho-sib/", "type": [ "Repository" ], "note": "neXtProt software repository with issue tracking" }, { "url": "https://twitter.com/nextprot_news", "type": [ "Social media" ], "note": "neXtProt release news, publications, presentations, tips and more. DM us with feedback!" }, { "url": "https://www.expasy.org/resources/nextprot", "type": [ "Software catalogue" ], "note": "neXtProt entry in Expasy" } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkz995", "pmid": "31724716", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The neXtProt knowledgebase in 2020: Data, tools and usability improvements", "abstract": "The neXtProt knowledgebase (https://www.nextprot.org) is an integrative resource providing both data on human protein and the tools to explore these. In order to provide comprehensive and up-to-date data, we evaluate and add new data sets. We describe the incorporation of three new data sets that provide expression, function, protein-protein binary interaction, post-translational modifications (PTM) and variant information. New SPARQL query examples illustrating uses of the new data were added. neXtProt has continued to develop tools for proteomics. We have improved the peptide uniqueness checker and have implemented a new protein digestion tool. Together, these tools make it possible to determine which proteases can be used to identify trypsin-resistant proteins by mass spectrometry. In terms of usability, we have finished revamping our web interface and completely rewritten our API. Our SPARQL endpoint now supports federated queries. All the neXtProt data are available via our user interface, API, SPARQL endpoint and FTP site, including the new PEFF 1.0 format files. Finally, the data on our FTP site is now CC BY 4.0 to promote its reuse.", "date": "2020-01-01T00:00:00Z", "citationCount": 155, "authors": [ { "name": "Zahn-Zabal M." }, { "name": "Michel P.-A." }, { "name": "Gateau A." }, { "name": "Nikitin F." }, { "name": "Schaeffer M." }, { "name": "Audot E." }, { "name": "Gaudet P." }, { "name": "Duek P.D." }, { "name": "Teixeira D." }, { "name": "De Laval V.R." }, { "name": "Samarasinghe K." }, { "name": "Bairoch A." }, { "name": "Lane L." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkr1179", "pmid": "22139911", "pmcid": "PMC3245017", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "NeXtProt: A knowledge platform for human proteins", "abstract": "neXtProt (http://www.nextprot.org/) is a new human protein-centric knowledge platform. Developed at the Swiss Institute of Bioinformatics (SIB), it aims to help researchers answer questions relevant to human proteins. To achieve this goal, neXtProt is built on a corpus containing both curated knowledge originating from the UniProtKB/Swiss-Prot knowledgebase and carefully selected and filtered high-throughput data pertinent to human proteins. This article presents an overview of the database and the data integration process. We also lay out the key future directions of neXtProt that we consider the necessary steps to make neXtProt the one-stop-shop for all research projects focusing on human proteins. © The Author(s) 2011.", "date": "2012-01-01T00:00:00Z", "citationCount": 168, "authors": [ { "name": "Lane L." }, { "name": "Argoud-Puy G." }, { "name": "Britan A." }, { "name": "Cusin I." }, { "name": "Duek P.D." }, { "name": "Evalet O." }, { "name": "Gateau A." }, { "name": "Gaudet P." }, { "name": "Gleizes A." }, { "name": "Masselot A." }, { "name": "Zwahlen C." }, { "name": "Bairoch A." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "SIB Swiss Institute of Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Support", "email": "support@nextprot.org", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Pascale Gaudet", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0003-1813-6857", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "SIB", "additionDate": "2015-01-21T13:30:06Z", "lastUpdate": "2025-04-02T08:05:19.163091Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "mzahn", "LanfearJ" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "csdR", "description": "Differential gene coexpression analysis based on the Conserved, Specific, and Differentiated (CSD) method", "homepage": "https://almaaslab.github.io/csdR/", "biotoolsID": "csdr", "biotoolsCURIE": "biotools:csdr", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" }, { "uri": "http://edamontology.org/topic_0085", "term": "Functional genomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.bioconductor.org/packages/release/bioc/html/csdR.html", "type": [ "Software catalogue" ], "note": null }, { "url": "https://github.com/AlmaasLab/csdR", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/s12859-022-04605-1", "pmid": "35183100", "pmcid": "PMC8858518", "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "csdR, an R package for differential co-expression analysis", "abstract": "Background: Differential co-expression network analysis has become an important tool to gain understanding of biological phenotypes and diseases. The CSD algorithm is a method to generate differential co-expression networks by comparing gene co-expressions from two different conditions. Each of the gene pairs is assigned conserved (C), specific (S) and differentiated (D) scores based on the co-expression of the gene pair between the two conditions. The result of the procedure is a network where the nodes are genes and the links are the gene pairs with the highest C-, S-, and D-scores. However, the existing CSD-implementations suffer from poor computational performance, difficult user procedures and lack of documentation. Results: We created the R-package csdR aimed at reaching good performance together with ease of use, sufficient documentation, and with the ability to play well with other tools for data analysis. csdR was benchmarked on a realistic dataset with 20,645 genes. After verifying that the chosen number of iterations gave sufficient robustness, we tested the performance against the two existing CSD implementations. csdR was superior in performance to one of the implementations, whereas the other did not run. Our implementation can utilize multiple processing cores. However, we were unable to achieve more than ∼ 2.7 parallel speedup with saturation reached at about 10 cores. Conclusion: The results suggest that csdR is a useful tool for differential co-expression analysis and is able to generate robust results within a workday on datasets of realistic sizes when run on a workstation or compute server.", "date": "2022-12-01T00:00:00Z", "citationCount": 3, "authors": [ { "name": "Pettersen J.P." }, { "name": "Almaas E." } ], "journal": "BMC Bioinformatics" } } ], "credit": [], "owner": "japet", "additionDate": "2025-03-31T08:50:20.800385Z", "lastUpdate": "2025-03-31T09:00:57.202555Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Species Search Engine - KISSE", "description": "KISSE is a species search engine that utilizes collagen sequences from eight different species to identify unknown samples.", "homepage": "https://kisse.serve.scilifelab.se/app/kisse", "biotoolsID": "kisse", "biotoolsCURIE": "biotools:kisse", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/hassanakthv/SIPMS", "type": "Source code", "note": null, "version": null } ], "documentation": [], "publication": [], "credit": [], "owner": "egonw", "additionDate": "2025-03-27T13:31:15.690258Z", "lastUpdate": "2025-03-28T21:26:36.097092Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Titania", "description": "Suite for In Silico Property Prediction and NAM-Based Modeling", "homepage": "https://enaloscloud.novamechanics.com/EnalosWebApps/titania/", "biotoolsID": "titania", "biotoolsCURIE": "biotools:titania", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3438", "term": "Calculation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2301", "term": "SMILES string" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0883", "term": "Structure" }, "format": [] } ], "note": "calculate boiling point", "cmd": "calculate boiling point" } ], "toolType": [], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "egonw", "additionDate": "2025-03-27T13:48:04.671506Z", "lastUpdate": "2025-03-28T21:26:03.296975Z", "editPermission": { "type": "group", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "WeSA", "description": "WeSA, (weighted socioaffinity), is a statistical score which can rank results from protein experiments of the bait-prey type, e.g. affinity purification, immunoprecipitation or proximity labelling.\n\nYou can enter lists of interacting proteins according to the results of your experiment. Input your raw data before any filtering is done.\n\nAs a result you will get a re-ordered list of scores which allows one to understand which interactions are more likely than others based on what previous experiments can add to your data.", "homepage": "https://wesa.russelllab.org/", "biotoolsID": "we_sa", "biotoolsCURIE": "biotools:we_sa", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3957", "term": "Protein interaction experiment" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/russelllab/wesa", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://wesa.russelllab.org/help", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkae423", "pmid": "38795065", "pmcid": "PMC11223876", "type": [], "version": null, "note": null, "metadata": { "title": "WeSA: A web server for improving analysis of affinity proteomics data", "abstract": "Protein-protein interaction experiments still yield many false positive interactions. The socioaffinity metric can distinguish true protein-protein interactions from noise based on available data. Here, we present WeSA (Weighted SocioAffinity), which considers large datasets of interaction proteomics data (IntAct, BioGRID, the BioPlex) to score human protein interactions and, in a statistically robust way, flag those (even from a single experiment) that are likely to be false positives. ROC analysis (using CORUM-PDB positives and Negatome negatives) shows that WeSA improves over other measures of interaction confidence. WeSA shows consistently good results over all datasets (up to: AUC = 0.93 and at best threshold: TPR = 0.84, FPR = 0.11, Precision = 0.98). WeSA is freely available without login (wesa.russelllab.org). Users can submit their own data or look for organized information on human protein interactions using the web server. Users can either retrieve available information for a list of proteins of interest or calculate scores for new experiments. The server outputs either pre-computed or updated WeSA scores for the input enriched with information from databases. The summary is presented as a table and a network-based visualization allowing the user to remove those nodes/edges that the method considers spurious.", "date": "2024-07-05T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Shtetinska M.M." }, { "name": "Gonzalez-Sanchez J.-C." }, { "name": "Beyer T." }, { "name": "Boldt K." }, { "name": "Ueffing M." }, { "name": "Russell R.B." } ], "journal": "Nucleic Acids Research" } } ], "credit": [], "owner": "Pub2Tools", "additionDate": "2025-03-28T11:13:12.813456Z", "lastUpdate": "2025-03-28T12:14:32.901305Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "ChemFH", "description": "An integrated online platform developed for the screening and prediction of potential frequent drug hitters, thus improving the efficiency of drug R&D in colloidal aggregate, firefly luciferase reporter enzyme inhibition, fluorescence, chemical reactivity, and promiscuity. ChemFH: an integrated tool for screening frequent false positives in chemical biology and drug discovery.", "homepage": "https://chemfh.scbdd.com/", "biotoolsID": "chemfh", "biotoolsCURIE": "biotools:chemfh", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3938", "term": "Virtual screening" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2301", "term": "SMILES string" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1696", "term": "Drug report" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1712", "term": "Chemical structure image" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Script", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0209", "term": "Medicinal chemistry" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "JavaScript" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/antwiser/ChemFH", "type": [ "Repository" ], "note": null }, { "url": "https://chemfh.scbdd.com/", "type": [ "Other" ], "note": "Webpage of the tool" } ], "download": [ { "url": "https://github.com/antwiser/ChemFH/releases/tag/ChemFH-1.0.0", "type": "Source code", "note": null, "version": "1.0.0" } ], "documentation": [ { "url": "https://github.com/antwiser/ChemFH/blob/main/README.md", "type": [ "General" ], "note": null }, { "url": "https://chemfh.scbdd.com/documentation/#/", "type": [ "Quick start guide" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkae424", "pmid": "38783035", "pmcid": "PMC11223804", "type": [ "Method" ], "version": "1.0.0", "note": "High-throughput screening rapidly tests an extensive array of chemical compounds to identify hit compounds for specific biological targets in drug discovery. However, false-positive results disrupt hit compound screening, leading to wastage of time and resources. To address this, we propose ChemFH, an integrated online platform facilitating rapid virtual evaluation of potential false positives, including colloidal aggregators, spectroscopic interference compounds, firefly luciferase inhibitors, chemical reactive compounds, promiscuous compounds, and other assay interferences. ChemFH is freely available via https://chemfh.scbdd.com/.", "metadata": { "title": "ChemFH: An integrated tool for screening frequent false positives in chemical biology and drug discovery", "abstract": "High-throughput screening rapidly tests an extensive array of chemical compounds to identify hit compounds for specific biological targets in drug discovery. However, false-positive results disrupt hit compound screening, leading to wastage of time and resources. To address this, we propose ChemFH, an integrated online platform facilitating rapid virtual evaluation of potential false positives, including colloidal aggregators, spectroscopic interference compounds, firefly luciferase inhibitors, chemical reactive compounds, promiscuous compounds, and other assay interferences. By leveraging a dataset containing 823 391 compounds, we constructed high-quality prediction models using multi-task directed message-passing network (DMPNN) architectures combining uncertainty estimation, yielding an average AUC value of 0.91. Furthermore, ChemFH incorporated 1441 representative alert substructures derived from the collected data and ten commonly used frequent hitter screening rules. ChemFH was validated with an external set of 75 compounds. Subsequently, the virtual screening capability of ChemFH was successfully confirmed through its application to five virtual screening libraries. Furthermore, ChemFH underwent additional validation on two natural products and FDA-approved drugs, yielding reliable and accurate results. ChemFH is a comprehensive, reliable, and computationally efficient screening pipeline that facilitates the identification of true positive results in assays, contributing to enhanced efficiency and success rates in drug discovery. ChemFH is freely available via https://chemfh.scbdd.com/.", "date": "2024-07-05T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Shi S." }, { "name": "Fu L." }, { "name": "Yi J." }, { "name": "Yang Z." }, { "name": "Zhang X." }, { "name": "Deng Y." }, { "name": "Wang W." }, { "name": "Wu C." }, { "name": "Zhao W." }, { "name": "Hou T." }, { "name": "Zeng X." }, { "name": "Lyu A." }, { "name": "Cao D." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Jiacai Yi", "email": "yjc@nudt.edu.cn", "url": "https://github.com/antwiser", "orcidid": "https://orcid.org/0000-0001-6823-1882", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "National University of Defense Technology, Changsha, Hunan" } ], "owner": "etepf22", "additionDate": "2025-03-28T11:01:52.929561Z", "lastUpdate": "2025-03-28T12:04:07.529430Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "LncRNAway", "description": "A web-based sgRNA design tool for precise and effective suppression of long noncoding RNAs", "homepage": "https://www.lncrnaway.com", "biotoolsID": "lncrnaway", "biotoolsCURIE": "biotools:lncrnaway", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0230", "term": "Sequence generation" }, { "uri": "http://edamontology.org/operation_0308", "term": "PCR primer design" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1033", "term": "Ensembl gene ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1026", "term": "Gene symbol" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3495", "term": "RNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_2305", "term": "GFF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3495", "term": "RNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_0972", "term": "Text mining report" }, "format": [] } ], "note": "Design of sgRNA for lncRNA knockout; Primer design for PCR and qPCR to knockout detection.", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0085", "term": "Functional genomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.lncrnaway.com", "type": [ "Service" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkae383", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "LncRNAway: A web-based sgRNA design tool for precise and effective suppression of long noncoding RNAs", "abstract": "Thousands of long noncoding RNAs (lncRNAs) have been annotated via high-throughput RNA sequencing, yet only a small fraction have been functionally investigated. Genomic knockout is the mainstream strategy for studying the biological function of protein-coding genes and lncRNAs, whereas the complexity of the lncRNA locus, especially the natural antisense lncRNAs (NAT-lncRNAs), presents great challenges. Knocking out lncRNAs often results in unintended disruptions of neighboring protein-coding genes and small RNAs, leading to ambiguity in observing phenotypes and interpreting biological function. To address this issue, we launched LncRNAway, a user-friendly web tool based on the BESST (branchpoint to 3' splicing site targeting) method, to design sgRNAs for lncRNA knockout. LncRNAway not only provides specific and effective lncRNA knockout guidelines but also integrates genotyping primers and quantitative PCR primers designing, thereby streamlining experimental procedures of lncRNA function study. 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Job Submission", "cmd": "$ curl https://biosig.lab.uq.edu.au/ddmut_ppi/api/single -X POST -i -F pdb_file=@/home/ubuntu/1cse.pdb -F mutation=L45G -F chain=I -F reverse=True" } ], "toolType": [ "Web API" ], "topic": [ { "uri": "http://edamontology.org/topic_3332", "term": "Computational chemistry" } ], "operatingSystem": [ "Linux" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://biosig.lab.uq.edu.au/ddmut_ppi/datasets", "type": "Biological data", "note": null, "version": null } ], "documentation": [ { "url": "https://biosig.lab.uq.edu.au/ddmut_ppi/api", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkae412", "pmid": "38783112", "pmcid": "PMC11223791", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "DDMut-PPI: Predicting effects of mutations on protein-protein interactions using graph-based deep learning", "abstract": "Protein-protein interactions (PPIs) play a vital role in cellular functions and are essential for therapeutic development and understanding diseases. However, current predictive tools often struggle to balance efficiency and precision in predicting the effects of mutations on these complex interactions. To address this, we present DDMut-PPI, a deep learning model that efficiently and accurately predicts changes in PPI binding free energy upon single and multiple point mutations. Building on the robust Siamese network architecture with graph-based signatures from our prior work, DDMut, the DDMut-PPI model was enhanced with a graph convolutional network operated on the protein interaction interface. We used residue-specific embeddings from ProtT5 protein language model as node features, and a variety of molecular interactions as edge features. By integrating evolutionary context with spatial information, this framework enables DDMut-PPI to achieve a robust Pearson correlation of up to 0.75 (root mean squared error: 1.33 kcal/mol) in our evaluations, outperforming most existing methods. Importantly, the model demonstrated consistent performance across mutations that increase or decrease binding affinity. DDMut-PPI offers a significant advancement in the field and will serve as a valuable tool for researchers probing the complexities of protein interactions. DDMut-PPI is freely available as a web server and an application programming interface at https://biosig.lab.uq.edu.au/ddmut_ppi.", "date": "2024-07-05T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Zhou Y." }, { "name": "Myung Y." }, { "name": "Rodrigues C.H.M." }, { "name": "Ascher D.B." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": null, "email": null, "url": "https://biosig.lab.uq.edu.au/contact", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "TomasGeraldes", "additionDate": "2025-03-28T11:04:18.911217Z", "lastUpdate": "2025-03-28T11:05:03.279672Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "prolfquapp", "description": "A command-line tool for differential expression analysis in quantitative proteomics", "homepage": "https://github.com/prolfqua/prolfquapp", "biotoolsID": "prolfquapp", "biotoolsCURIE": "biotools:prolfquapp", "version": [ "0.1.6" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3741", "term": "Differential protein expression profiling" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3620", "term": "xlsx" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": "./prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y config.yaml -w NameOfAnalysis -s DIANN\n# and again you run the version within the docker container with\n# ./prolfquapp_docker.sh prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y config.yaml -w NameOfAnalysis -s DIANN" }, { "operation": [ { "uri": "http://edamontology.org/operation_2428", "term": "Validation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3620", "term": "xlsx" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3914", "term": "Quality control report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0571", "term": "Expression data visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "R" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/prolfqua/prolfquapp", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/prolfqua/prolfquapp/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/prolfqua/prolfquapp/releases/tag/0.1.6", "type": "Downloads page", "note": null, "version": "0.1.6" } ], "documentation": [ { "url": "https://github.com/prolfqua/prolfquapp/blob/master/README.md", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jproteome.4c00911", "pmid": null, "pmcid": null, "type": [], "version": "0.0.6", "note": null, "metadata": { "title": "prolfquapp ─ A User-Friendly Command-Line Tool Simplifying Differential Expression Analysis in Quantitative Proteomics", "abstract": "Mass spectrometry is a cornerstone of quantitative proteomics, enabling relative protein quantification and differential expression analysis (DEA) of proteins. As experiments grow in complexity, involving more samples, groups, and identified proteins, interactive differential expression analysis tools become impractical. The prolfquapp addresses this challenge by providing a command-line interface that simplifies DEA, making it accessible to nonprogrammers and seamlessly integrating it into workflow management systems. Prolfquapp streamlines data processing and result visualization by generating dynamic HTML reports that facilitate the exploration of differential expression results. These reports allow for investigating complex experiments, such as those involving repeated measurements or multiple explanatory variables. Additionally, prolfquapp supports various output formats, including XLSX files, SummarizedExperiment objects and rank files, for further interactive analysis using spreadsheet software, the exploreDE Shiny application, or gene set enrichment analysis software, respectively. By leveraging advanced statistical models from the prolfqua R package, prolfquapp offers a user-friendly, integrated solution for large-scale quantitative proteomics studies, combining efficient data processing with insightful, publication-ready outputs.", "date": "2025-02-07T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Wolski W.E." }, { "name": "Grossmann J." }, { "name": "Schwarz L." }, { "name": "Leary P." }, { "name": "Turker C." }, { "name": "Nanni P." }, { "name": "Schlapbach R." }, { "name": "Panse C." } ], "journal": "Journal of Proteome Research" } } ], "credit": [], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2025-02-28T15:04:33.594183Z", "lastUpdate": "2025-03-28T10:18:25.715685Z", "editPermission": { "type": "group", "authors": [ "thatmariia" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "WorkflowHub", "description": "WorkflowHub is a registry for describing, sharing and publishing scientific computational workflows.\n\nThe registry supports any workflow in its native repository.\n\nWorkflowHub aims to facilitate discovery and re-use of workflows in an accessible and interoperable way. 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It provides:\n* periodic testing;\n* test monitoring and notification;\n* automated checks and templates for workflow best practices.", "homepage": "https://lifemonitor.eu", "biotoolsID": "lifemonitor", "biotoolsCURIE": "biotools:lifemonitor", "version": [], "otherID": [], "relation": [ { "biotoolsID": "rocrate-validator", "type": "uses" } ], "function": [], "toolType": [ "Web application", "Web API", "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_3372", "term": "Software engineering" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" }, { "uri": "http://edamontology.org/topic_4010", "term": "Open science" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python", "JavaScript" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/crs4/life_monitor", "type": [ "Repository" ], "note": null }, { "url": "https://api.lifemonitor.eu", "type": [ "Service" ], "note": "REST API (production instance)" }, { "url": "https://api.dev/lifemonitor.eu", "type": [ "Service" ], "note": "REST API (dev instance)" }, { "url": "https://app.lifemonitor.eu", "type": [ "Service" ], "note": "Web App (production instance)" }, { "url": "https://app.dev.lifemonitor.eu", "type": [ "Service" ], "note": "Web App (dev instance)" }, { "url": "https://github.com/crs4/life_monitor/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/apps/lifemonitor", "type": [ "Service" ], "note": "GitHub App" } ], "download": [], "documentation": [ { "url": "https://lifemonitor.eu", "type": [ "User manual" ], "note": null }, { "url": "https://api.lifemonitor.eu/openapi.html", "type": [ "API documentation" ], "note": null } ], "publication": [], "credit": [ { "name": "Marco Enrico Piras", "email": "marcoenrico.piras@crs4.it", "url": null, "orcidid": "https://orcid.org/0000-0002-5207-0030", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "Simone Leo", "email": "simone.leo@crs4.it", "url": null, "orcidid": "https://orcid.org/0000-0001-8271-5429", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Developer" ], "note": null }, { "name": "Luca Pireddu", "email": "luca.pireddu@crs4.it", "url": null, "orcidid": "https://orcid.org/0000-0002-4663-5613", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Developer" ], "note": null }, { "name": "CRS4", "email": null, "url": "https://www.crs4.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null }, { "name": "EOSC-Life", "email": null, "url": "https://www.eosc-life.eu/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [], "note": null } ], "owner": "mep", "additionDate": "2025-03-25T12:17:42.278603Z", "lastUpdate": "2025-03-25T12:17:42.289116Z", "editPermission": { "type": "group", "authors": [ "mep", "ilveroluca" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "The MINERVA Platform", "description": "The MINERVA (Molecular Interaction NEtwoRk VisuAlization) platform is a standalone webserver for visualization, exploration and management of molecular networks encoded in SBGN-compliant format, including files produced using CellDesigner or SBGN editors. Visualization of uploaded networks generated by the platform is accessible via a web browser to all viewers with the weblink to the resource.\n\nThe MINERVA Platform is a webservice using the Java Server Faces 2 technology. The server side, including data parsing, integration, annotation and verification, is implemented in Java. The platform uses the Postgres SQL database for data storage and the Hibernate framework as a middle layer between web server and database. The user web-interface is generated using React.js. The displayed content is visualized by OpenLayers API, dedicated JavaScript and CSS.", "homepage": "https://minerva.uni.lu", "biotoolsID": "MINERVA_Platform", "biotoolsCURIE": "biotools:MINERVA_Platform", "version": [ "13.1.3", "13.2.0", "14.0.13", "15.0.3", "16.4.0", "17.1.3", "18.1.1" ], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_3391", "term": "Omics" }, { "uri": "http://edamontology.org/topic_3342", "term": "Translational medicine" } ], "operatingSystem": [], "language": [], "license": "AGPL-3.0", "collectionID": [ "ELIXIR-LU", "LCSB" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Luxembourg" ], "elixirCommunity": [], "link": [ { "url": "https://gitlab.lcsb.uni.lu/minerva/core/", "type": [ "Repository" ], "note": "GiLab repository for core functionalities (data and format handling, service stability, API access)" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/core/-/issues", "type": [ "Issue tracker" ], "note": "Issue tracker for core functionalities (data and format handling, service stability, API access)" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/frontend", "type": [ "Repository" ], "note": "GiLab repository for frontend functionalities" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/frontend/-/issues", "type": [ "Issue tracker" ], "note": "Issue tracker for frontend functionalities" } ], "download": [ { "url": "https://minerva.pages.uni.lu/doc/install/", "type": "Other", "note": "Installation instructions, including debian package, virtual machine images and docker containers.", "version": "13.1.3 - 18.1.1" } ], "documentation": [ { "url": "https://minerva.uni.lu", "type": [ "Quick start guide", "Release notes", "User manual", "API documentation", "Citation instructions", "Terms of use" ], "note": null } ], "publication": [ { "doi": "10.1038/npjsba.2016.20", "pmid": "28725475", "pmcid": "PMC5516855", "type": [ "Primary" ], "version": "10.0", "note": null, "metadata": { "title": "MINERVA—A platform for visualization and curation of molecular interaction networks", "abstract": "Our growing knowledge about various molecular mechanisms is becoming increasingly more structured and accessible. Different repositories of molecular interactions and available literature enable construction of focused and high-quality molecular interaction networks. Novel tools for curation and exploration of such networks are needed, in order to foster the development of a systems biology environment. In particular, solutions for visualization, annotation and data cross-linking will facilitate usage of network-encoded knowledge in biomedical research. To this end we developed the MINERVA (Molecular Interaction NEtwoRks VisuAlization) platform, a standalone webservice supporting curation, annotation and visualization of molecular interaction networks in Systems Biology Graphical Notation (SBGN)-compliant format. MINERVA provides automated content annotation and verification for improved quality control. The end users can explore and interact with hosted networks, and provide direct feedback to content curators. MINERVA enables mapping drug targets or overlaying experimental data on the visualized networks. Extensive export functions enable downloading areas of the visualized networks as SBGN-compliant models for efficient reuse of hosted networks. The software is available under Affero GPL 3.0 as a Virtual Machine snapshot, Debian package and Docker instance at http://r3lab.uni.lu/web/minerva-website/. We believe that MINERVA is an important contribution to systems biology community, as its architecture enables set-up of locally or globally accessible SBGN-oriented repositories of molecular interaction networks. Its functionalities allow overlay of multiple information layers, facilitating exploration of content and interpretation of data. Moreover, annotation and verification workflows of MINERVA improve the efficiency of curation of networks, allowing life-science researchers to better engage in development and use of biomedical knowledge repositories.", "date": "2016-01-01T00:00:00Z", "citationCount": 60, "authors": [ { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Satagopam V." }, { "name": "Gebel S." }, { "name": "Mazein A." }, { "name": "Kuzma M." }, { "name": "Zorzan S." }, { "name": "McGee F." }, { "name": "Otjacques B." }, { "name": "Balling R." }, { "name": "Schneider R." } ], "journal": "npj Systems Biology and Applications" } }, { "doi": "10.1093/bioinformatics/btz286", "pmid": "31074494", "pmcid": "PMC6821317", "type": [ "Primary" ], "version": "12.2.3", "note": null, "metadata": { "title": "MINERVA API and plugins: Opening molecular network analysis and visualization to the community", "abstract": "Summary: The complexity of molecular networks makes them difficult to navigate and interpret, creating a need for specialized software. MINERVA is a web platform for visualization, exploration and management of molecular networks. Here, we introduce an extension to MINERVA architecture that greatly facilitates the access and use of the stored molecular network data. It allows to incorporate such data in analytical pipelines via a programmatic access interface, and to extend the platform's visual exploration and analytics functionality via plugin architecture. This is possible for any molecular network hosted by the MINERVA platform encoded in well-recognized systems biology formats. To showcase the possibilities of the plugin architecture, we have developed several plugins extending the MINERVA core functionalities. In the article, we demonstrate the plugins for interactive tree traversal of molecular networks, for enrichment analysis and for mapping and visualization of known disease variants or known adverse drug reactions to molecules in the network. Availability and implementation: Plugins developed and maintained by the MINERVA team are available under the AGPL v3 license at https://git-r3lab.uni.lu/minerva/plugins/. The MINERVA API and plugin documentation is available at https://minerva-web.lcsb.uni.lu.", "date": "2019-11-01T00:00:00Z", "citationCount": 24, "authors": [ { "name": "Hoksza D." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Smula E." }, { "name": "Schneider R." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bib/bbz067", "pmid": "31273380", "pmcid": "PMC7373180", "type": [ "Primary" ], "version": "13.1.1", "note": null, "metadata": { "title": "Closing the gap between formats for storing layout information in systems biology", "abstract": "The understanding of complex biological networks often relies on both a dedicated layout and a topology. Currently, there are three major competing layout-aware systems biology formats, but there are no software tools or software libraries supporting all of them. This complicates the management of molecular network layouts and hinders their reuse and extension. In this paper, we present a high-level overview of the layout formats in systems biology, focusing on their commonalities and differences, review their support in existing software tools, libraries and repositories and finally introduce a new conversion module within the MINERVA platform. The module is available via a REST API and offers, besides the ability to convert between layout-aware systems biology formats, the possibility to export layouts into several graphical formats. The module enables conversion of very large networks with thousands of elements, such as disease maps or metabolic reconstructions, rendering it widely applicable in systems biology.", "date": "2019-07-10T00:00:00Z", "citationCount": 15, "authors": [ { "name": "Hoksza D." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Hasenauer J." }, { "name": "Schneider R." } ], "journal": "Briefings in Bioinformatics" } }, { "doi": "10.1089/big.2015.0057", "pmid": "27441714", "pmcid": "PMC4932659", "type": [ "Usage" ], "version": "10.0", "note": null, "metadata": { "title": "Integration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases", "abstract": "Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services - tranSMART, a Galaxy Server, and a MINERVA platform - are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and disease-related mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data.", "date": "2016-06-01T00:00:00Z", "citationCount": 38, "authors": [ { "name": "Satagopam V." }, { "name": "Gu W." }, { "name": "Eifes S." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Gebel S." }, { "name": "Barbosa-Silva A." }, { "name": "Balling R." }, { "name": "Schneider R." } ], "journal": "Big Data" } }, { "doi": "10.1016/j.envpol.2019.04.005", "pmid": "30991279", "pmcid": null, "type": [], "version": "13.1.1", "note": null, "metadata": { "title": "Genes associated with Parkinson's disease respond to increasing polychlorinated biphenyl levels in the blood of healthy females", "abstract": "Polychlorinated biphenyls (PCBs) are a class of widespread environmental pollutants, commonly found in human blood, that have been suggested to be linked to the occurrence of sporadic Parkinson's disease (PD). It has been reported that some non-coplanar PCBs accumulate in the brains of female PD patients. To improve our understanding of the association between PCB exposure and PD risk we have applied whole transcriptome gene expression analysis in blood cells from 594 PCB-exposed subjects (369 female, 225 male). Interestingly, we observe that in females, blood levels of non-coplanar PCBs appear to be associated with expression levels of PD-specific genes. However, no such association was detected in males. Among the 131 PD-specific genes affected, 39 have been shown to display similar changes in expression levels in the substantia nigra of deceased PD patients. Especially among the down-regulated genes, transcripts of genes involved in neurotransmitter vesicle-related functions were predominant. Capsule: Plasma PCB levels are associated with gene expression changes in females only, resulting in brain-related genes changing in blood cells of healthy individuals exposed to PCBs.", "date": "2019-07-01T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Bohler S." }, { "name": "Krauskopf J." }, { "name": "Espin-Perez A." }, { "name": "Gebel S." }, { "name": "Palli D." }, { "name": "Rantakokko P." }, { "name": "Kiviranta H." }, { "name": "Kyrtopoulos S.A." }, { "name": "Balling R." }, { "name": "Kleinjans J." } ], "journal": "Environmental Pollution" } } ], "credit": [], "owner": "mjostaszewski", "additionDate": "2019-08-26T14:34:55Z", "lastUpdate": "2025-03-24T08:35:28.416761Z", "editPermission": { "type": "group", "authors": [ "sascha.herzinger" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DISULFIND", "description": "DISULFIND is a server for predicting the disulfide bonding state of cysteines and their disulfide connectivity given a protein sequence.", "homepage": "http://disulfind.dsi.unifi.it/", "biotoolsID": "disulfind", "biotoolsCURIE": "biotools:disulfind", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2479", "term": "Protein sequence analysis" }, { "uri": "http://edamontology.org/operation_2423", "term": "Prediction and recognition" }, { "uri": "http://edamontology.org/operation_1850", "term": "Protein cysteine and disulfide bond assignment" }, { "uri": "http://edamontology.org/operation_3092", "term": "Protein feature detection" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_3510", "term": "Protein sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0157", "term": "Sequence composition, complexity and repeats" }, { "uri": "http://edamontology.org/topic_0623", "term": "Gene and protein families" }, { "uri": "http://edamontology.org/topic_0082", "term": "Structure prediction" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://disulfind.dsi.unifi.it/help.php", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkl266", "pmid": "16844986", "pmcid": "PMC1538823", "type": [], "version": null, "note": null, "metadata": null }, { "doi": "10.1093/bioinformatics/btg463", "pmid": "15033872", "pmcid": null, "type": [], "version": null, "note": null, "metadata": null }, { "doi": "10.1093/nar/gkr365", "pmid": "21576237", "pmcid": "PMC3125771", "type": [], "version": null, "note": null, "metadata": null }, { "doi": "10.1093/bioinformatics/btn371", "pmid": "18635571", "pmcid": "PMC2732205", "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "DISULFIND Support", "email": "disulfind@ai.dinfo.unifi.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-EE", "additionDate": "2017-02-10T14:15:18Z", "lastUpdate": "2025-03-23T11:05:22.310421Z", "editPermission": { "type": "group", "authors": [ "schmidt" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DeepAnnotation", "description": "The python package 'DeepAnnotation' can be used to perform genomic selection (GS), which is a promising breeding strategy for agricultural breeding. DeepAnnotation predicts phenotypes from comprehensive multi-omics functional annotations with interpretable deep learning framework.", "homepage": "https://github.com/mawenlong2016/DeepAnnotation", "biotoolsID": "deepannotation", "biotoolsCURIE": "biotools:deepannotation", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool", "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" } ], "operatingSystem": [], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/mawenlong2016/DeepAnnotation", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/mawenlong2016/DeepAnnotation", "type": "Downloads page", "note": "GitHub repository", "version": null } ], "documentation": [], "publication": [], "credit": [], "owner": "mawenlong2025", "additionDate": "2025-03-22T00:35:21.183948Z", "lastUpdate": "2025-03-22T00:35:21.186342Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Spacedust", "description": "Spacedust is a modular toolkit for identification of conserved gene clusters among multiple genomes based on homology and conservation of gene neighborhood. Spacedust adapts the fast and sensitive structure comparisons of Foldseek and homology search capabilities of MMseqs2. It introduces a novel approach of aggregating sets of homologous hits between pairs of genomes and identifies cluster of hits with conserved gene neighborhood between each using agglomerative hierarchical clustering algorithm.", "homepage": "https://github.com/soedinglab/spacedust/", "biotoolsID": "spacedust", "biotoolsCURIE": "biotools:spacedust", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "C++" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1101/2024.10.02.616292v1", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "milot-mirdita", "additionDate": "2025-03-20T09:46:51.356874Z", "lastUpdate": "2025-03-20T09:46:51.359476Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PPAI", "description": "PPAI is a web server for predicting protein-aptamer interactions.\n\nThe interactions between proteins and aptamers are prevalent in organisms and play an important role in various life activities. Thanks to the rapid accumulation of protein-aptamer interaction data, it is very important and feasible to construct an accurate computational model to predict protein-aptamer interactions, which is benefit for understanding mechanisms of protein-aptamer interactions and improving aptamer-based therapies.\n\nPPAI is a novel web-server to predict aptamers and protein-aptamer interactions with sequence features of proteins/aptamers and machine learning framework which integrated Adaboost and Random Forest. PPAI not only provides more accurate prediction functions, but also provides the protein aptamer information to the user for query.", "homepage": "http://39.96.85.9/PPAI", "biotoolsID": "ppai", "biotoolsCURIE": "biotools:ppai", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3092", "term": "Protein feature detection" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2492", "term": "Protein interaction prediction" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0253", "term": "Sequence feature detection" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/S12859-020-03574-7", "pmid": "32517696", "pmcid": "PMC7285591", "type": [], "version": null, "note": null, "metadata": { "title": "PPAI: A web server for predicting protein-aptamer interactions", "abstract": "Background: The interactions between proteins and aptamers are prevalent in organisms and play an important role in various life activities. Thanks to the rapid accumulation of protein-aptamer interaction data, it is necessary and feasible to construct an accurate and effective computational model to predict aptamers binding to certain interested proteins and protein-aptamer interactions, which is beneficial for understanding mechanisms of protein-aptamer interactions and improving aptamer-based therapies. Results: In this study, a novel web server named PPAI is developed to predict aptamers and protein-aptamer interactions with key sequence features of proteins/aptamers and a machine learning framework integrated adaboost and random forest. A new method for extracting several key sequence features of both proteins and aptamers is presented, where the features for proteins are extracted from amino acid composition, pseudo-amino acid composition, grouped amino acid composition, C/T/D composition and sequence-order-coupling number, while the features for aptamers are extracted from nucleotide composition, pseudo-nucleotide composition (PseKNC) and normalized Moreau-Broto autocorrelation coefficient. On the basis of these feature sets and balanced the samples with SMOTE algorithm, we validate the performance of PPAI by the independent test set. The results demonstrate that the Area Under Curve (AUC) is 0.907 for prediction of aptamer, while the AUC reaches 0.871 for prediction of protein-aptamer interactions. Conclusion: These results indicate that PPAI can query aptamers and proteins, predict aptamers and predict protein-aptamer interactions in batch mode precisely and efficiently, which would be a novel bioinformatics tool for the research of protein-aptamer interactions. PPAI web-server is freely available at http://39.96.85.9/PPAI.", "date": "2020-06-09T00:00:00Z", "citationCount": 14, "authors": [ { "name": "Li J." }, { "name": "Ma X." }, { "name": "Li X." }, { "name": "Gu J." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.21203/RS.3.RS-27174/V2", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Jianwei Li", "email": "lijianwei@hebut.edu.cn", "url": null, "orcidid": "https://orcid.org/0000-0002-9795-2635", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "zsmag19", "additionDate": "2021-01-18T09:26:31Z", "lastUpdate": "2025-03-20T07:27:32.204279Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "European Health Research Data and Sample Catalogue", "description": "A collaborative effort to integrate the catalogues of diverse EU research projects and networks to accelerate reuse and improve citizens health.", "homepage": "https://data-catalogue.molgeniscloud.org/", "biotoolsID": "molgenis_european_health_research_data_and_sample_catalogue", "biotoolsCURIE": "biotools:molgenis_european_health_research_data_and_sample_catalogue", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Database portal" ], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1055/s-0042-1742522", "pmid": "36463884", "pmcid": "PMC9719789", "type": [], "version": null, "note": null, "metadata": { "title": "Towards an Interoperable Ecosystem of Research Cohort and Real-world Data Catalogues Enabling Multi-center Studies", "abstract": "Objectives: Existing individual-level human data cover large populations on many dimensions such as lifestyle, demography, laboratory measures, clinical parameters, etc. Recent years have seen large investments in data catalogues to FAIRify data descriptions to capitalise on this great promise, i.e. make catalogue contents more Findable, Accessible, Interoperable and Reusable. However, their valuable diversity also created heterogeneity, which poses challenges to optimally exploit their richness. Methods: In this opinion review, we analyse catalogues for human subject research ranging from cohort studies to surveillance, administrative and healthcare records. Results: We observe that while these catalogues are heterogeneous, have various scopes, and use different terminologies, still the underlying concepts seem potentially harmonizable. We propose a unified framework to enable catalogue data sharing, with catalogues of multi-center cohorts nested as a special case in catalogues of real-world data sources. Moreover, we list recommendations to create an integrated community of metadata catalogues and an open catalogue ecosystem to sustain these efforts and maximise impact. Conclusions: We propose to embrace the autonomy of motivated catalogue teams and invest in their collaboration via minimal standardisation efforts such as clear data licensing, persistent identifiers for linking same records between catalogues, minimal metadata 'common data elements' using shared ontologies, symmetric architectures for data sharing (push/pull) with clear provenance tracks to process updates and acknowledge original contributors. And most importantly, we encourage the creation of environments for collaboration and resource sharing between catalogue developers, building on international networks such as OpenAIRE and research data alliance, as well as domain specific ESFRIs such as BBMRI and ELIXIR.", "date": "2022-12-04T00:00:00Z", "citationCount": 9, "authors": [ { "name": "Swertz M." }, { "name": "Van Enckevort E." }, { "name": "Oliveira J.L." }, { "name": "Fortier I." }, { "name": "Bergeron J." }, { "name": "Thurin N.H." }, { "name": "Hyde E." }, { "name": "Kellmann A." }, { "name": "Pahoueshnja R." }, { "name": "Sturkenboom M." }, { "name": "Cunnington M." }, { "name": "Nybo Andersen A.-M." }, { "name": "Marcon Y." }, { "name": "Goncalves G." }, { "name": "Gini R." } ], "journal": "Yearbook of Medical Informatics" } } ], "credit": [], "owner": "EleanorHyde", "additionDate": "2025-03-11T14:55:53.492167Z", "lastUpdate": "2025-03-19T15:08:24.036904Z", "editPermission": { "type": "group", "authors": [ "mswertz", "EleanorHyde" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MatHeat", "description": "MatHeat transforms your gene expression data into stunning interactive heatmaps with advanced clustering, UMAP/KMeans, and Reactome pathway analysis.", "homepage": "https://matheat.streamlit.app/", "biotoolsID": "matheat", "biotoolsCURIE": "biotools:matheat", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3574", "term": "Human genetics" }, { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_3372", "term": "Software engineering" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://matheat.streamlit.app/", "type": [ "Service" ], "note": null }, { "url": "https://amin-mat.github.io/matheat-landing/", "type": [ "Other" ], "note": "Landing page of the MatHeat" }, { "url": "https://matheat.org/", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [], "publication": [], "credit": [ { "name": "Seyyed Amin Seyyed Rezaei", "email": "seyyedamin1381@gmail.com", "url": "https://matheat.streamlit.app/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact", "Maintainer" ], "note": null } ], "owner": "Aminn", "additionDate": "2025-03-12T22:55:02.224894Z", "lastUpdate": "2025-03-19T15:07:19.209944Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "INPS-MD", "description": "Predicting the impact of mutations on protein stability from sequence and structure.", "homepage": "http://inpsmd.biocomp.unibo.it", "biotoolsID": "inps-md", "biotoolsCURIE": "biotools:inps-md", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [] } ], "note": "Prediction of the impact of non-synonymous polymorphisms on protein stability from sequence.", "cmd": null }, { "operation": [], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1008", "term": "Polypeptide chain ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [] } ], "note": "Prediction of the impact of non-synonymous polymorphisms on protein stability from structure.", "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0130", "term": "Protein folding, stability and design" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Italy" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "https://inpsmd.biocomp.unibo.it/help", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btv291", "pmid": "25957347", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "INPS: Predicting the impact of non-synonymous variations on protein stability from sequence", "abstract": "Motivation: A tool for reliably predicting the impact of variations on protein stability is extremely important for both protein engineering and for understanding the effects of Mendelian and somatic mutations in the genome. Next Generation Sequencing studies are constantly increasing the number of protein sequences. Given the huge disproportion between protein sequences and structures, there is a need for tools suited to annotate the effect of mutations starting from protein sequence without relying on the structure. Here, we describe INPS, a novel approach for annotating the effect of non-synonymous mutations on the protein stability from its sequence. INPS is based on SVM regression and it is trained to predict the thermodynamic free energy change upon single-point variations in protein sequences. Results: We show that INPS performs similarly to the state-of-the-art methods based on protein structure when tested in cross-validation on a non-redundant dataset. INPS performs very well also on a newly generated dataset consisting of a number of variations occurring in the tumor suppressor protein p53. Our results suggest that INPS is a tool suited for computing the effect of non-synonymous polymorphisms on protein stability when the protein structure is not available. We also show that INPS predictions are complementary to those of the state-of-the-art, structure-based method mCSM. When the two methods are combined, the overall prediction on the p53 set scores significantly higher than those of the single methods.", "date": "2015-02-06T00:00:00Z", "citationCount": 111, "authors": [ { "name": "Fariselli P." }, { "name": "Martelli P.L." }, { "name": "Savojardo C." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bioinformatics/btw192", "pmid": "27153629", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "INPS-MD: A web server to predict stability of protein variants from sequence and structure", "abstract": "Motivation: Protein function depends on its structural stability. The effects of single point variations on protein stability can elucidate the molecular mechanisms of human diseases and help in developing new drugs. Recently, we introduced INPS, a method suited to predict the effect of variations on protein stability from protein sequence and whose performance is competitive with the available state-of-the-art tools. Results: In this article, we describe INPS-MD (Impact of Non synonymous variations on Protein Stability-Multi-Dimension), a web server for the prediction of protein stability changes upon single point variation from protein sequence and/or structure. Here, we complement INPS with a new predictor (INPS3D) that exploits features derived from protein 3D structure. INPS3D scores with Pearson's correlation to experimental ΔΔG values of 0.58 in cross validation and of 0.72 on a blind test set. The sequence-based INPS scores slightly lower than the structure-based INPS3D and both on the same blind test sets well compare with the state-of-the-art methods.", "date": "2016-08-15T00:00:00Z", "citationCount": 189, "authors": [ { "name": "Savojardo C." }, { "name": "Fariselli P." }, { "name": "Martelli P.L." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "https://www.biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Piero Fariselli", "email": "piero.fariselli@unito.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Castrense Savojardo", "email": "savojard@biocomp.unibo.it", "url": "http://biocomp.unibo.it/savojard/", "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2016-05-04T15:36:53Z", "lastUpdate": "2025-03-19T15:01:04.207003Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-ITA-BOLOGNA", "savo", "Pub2Tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "EXPOSOME maps", "description": "The Exposome Maps contain geospatially resolved data on environmental exposures (Exposome Surfaces), categorized into the following Exposome dimensions:\nBuilt Environment28 exposures related to:\n•\tGreen space\n•\tBlue space\n•\tGrey space\nFood Environment4 exposures related to:\n•\tFood landscape / healthy food index\nPhysico-Chemical Environment99 exposures related to:\n•\tAir pollution\n•\tBiodiversity\n•\tWeather conditions\n•\tLight intensity at night\n•\tNoise\n•\tPesticides\n•\tElectromagnetic fields\nSocial Environment70 exposures related to:\n•\tNeighbourhood socio-economic position\n•\tNeighbourhood Demographic surfaces and population characteristics\n•\tSocial capital\n•\tSecurity\n•\tMental health\n•\tProximity to facilities\n•\tEnergy use\n•\tLabour market", "homepage": "https://exposome.dataplatform.nl/#/home", "biotoolsID": "exposome_maps", "biotoolsCURIE": "biotools:exposome_maps", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_4012", "term": "FAIR data" }, { "uri": "http://edamontology.org/topic_3855", "term": "Environmental sciences" } ], "operatingSystem": [], "language": [], "license": "Other", "collectionID": [], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Restricted access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://expanseproject.eu/", "type": [ "Other" ], "note": "Project information page" } ], "download": [], "documentation": [ { "url": "https://surfdrive.surf.nl/files/index.php/s/uqUORDrd428H2F9", "type": [ "User manual" ], "note": "Description of Environmental variables available through Exposome Maps" }, { "url": "https://surfdrive.surf.nl/files/index.php/s/fI0Gmuu5O1MJAI9", "type": [ "Terms of use" ], "note": "Exposome-NL data platform Data Access and Publication Policy" } ], "publication": [ { "doi": "10.1126/science.aay3164", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "The exposome and health: Where chemistry meets biology", "abstract": "Despite extensive evidence showing that exposure to specific chemicals can lead to disease, current research approaches and regulatory policies fail to address the chemical complexity of our world. To safeguard current and future generations from the increasing number of chemicals polluting our environment, a systematic and agnostic approach is needed. The “exposome” concept strives to capture the diversity and range of exposures to synthetic chemicals, dietary constituents, psychosocial stressors, and physical factors, as well as their corresponding biological responses. Technological advances such as high-resolution mass spectrometry and network science have allowed us to take the first steps toward a comprehensive assessment of the exposome. Given the increased recognition of the dominant role that nongenetic factors play in disease, an effort to characterize the exposome at a scale comparable to that of the human genome is warranted.", "date": "2020-01-24T00:00:00Z", "citationCount": 587, "authors": [ { "name": "Vermeulen R." }, { "name": "Schymanski E.L." }, { "name": "Barabasi A.-L." }, { "name": "Miller G.W." } ], "journal": "Science" } }, { "doi": "10.1097/EE9.0000000000000162", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Developing the building blocks to elucidate the impact of the urban exposome on cardiometabolic-pulmonary disease: The EU EXPANSE project", "abstract": "By 2030, more than 80% of Europe's population will live in an urban environment. The urban exposome, consisting of factors such as where we live and work, where and what we eat, our social network, and what chemical and physical hazards we are exposed to, provides important targets to improve population health. The EXPANSE (EXposome Powered tools for healthy living in urbAN SEttings) project will study the impact of the urban exposome on the major contributors to Europe's burden of disease: Cardio-Metabolic and Pulmonary Disease. EXPANSE will address one of the most pertinent questions for urban planners, policy makers, and European citizens: \"How to maximize one's health in a modern urban environment?\" EXPANSE will take the next step in exposome research by (1) bringing together exposome and health data of more than 55 million adult Europeans and OMICS information for more than 2 million Europeans; (2) perform personalized exposome assessment for 5,000 individuals in five urban regions; (3) applying ultra-high-resolution mass-spectrometry to screen for chemicals in 10,000 blood samples; (4) evaluating the evolution of the exposome and health through the life course; and (5) evaluating the impact of changes in the urban exposome on the burden of cardiometabolic and pulmonary disease. EXPANSE will translate its insights and innovations into research and dissemination tools that will be openly accessible via the EXPANSE toolbox. By applying innovative ethics-by-design throughout the project, the social and ethical acceptability of these tools will be safeguarded. EXPANSE is part of the European Human Exposome Network.", "date": "2021-08-01T00:00:00Z", "citationCount": 36, "authors": [ { "name": "Vlaanderen J." }, { "name": "De Hoogh K." }, { "name": "Hoek G." }, { "name": "Peters A." }, { "name": "Probst-Hensch N." }, { "name": "Scalbert A." }, { "name": "Melen E." }, { "name": "Tonne C." }, { "name": "De Wit G.A." }, { "name": "Chadeau-Hyam M." }, { "name": "Katsouyanni K." }, { "name": "Esko T." }, { "name": "Jongsma K.R." }, { "name": "Vermeulen R." } ], "journal": "Environmental Epidemiology" } } ], "credit": [ { "name": "Roel Vermeulen", "email": "R.C.H.Vermeulen@uu.nl", "url": null, "orcidid": "https://orcid.org/0000-0003-4082-8163", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact" ], "note": null }, { "name": "Zimbo Boudewijns", "email": "z.s.r.m.boudewijns@uu.nl", "url": null, "orcidid": "https://orcid.org/0000-0002-9383-9571", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Maintainer" ], "note": null }, { "name": "Lloyd Roga", "email": "l.q.roga@uu.nl", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null } ], "owner": "Channel2291", "additionDate": "2025-03-17T14:01:59.601345Z", "lastUpdate": "2025-03-19T14:50:02.027296Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "chewBBaca", "description": "chewBBACA is a software suite for the creation and evaluation of core genome and whole genome MultiLocus Sequence Typing (cg/wgMLST) schemas and results.", "homepage": "https://github.com/B-UMMI/chewBBACA", "biotoolsID": "chewbbaca", "biotoolsCURIE": "biotools:chewbbaca", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3840", "term": "Multilocus sequence typing" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://chewbbaca.readthedocs.io/en/latest/index.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1099/MGEN.0.000166", "pmid": "29543149", "pmcid": "PMC5885018", "type": [], "version": null, "note": null, "metadata": { "title": "chewBBACA: A complete suite for gene-by-gene schema creation and strain identification", "abstract": "Gene-by-gene approaches are becoming increasingly popular in bacterial genomic epidemiology and outbreak detection. However, there is a lack of open-source scalable software for schema definition and allele calling for these methodologies. The chewBBACA suite was designed to assist users in the creation and evaluation of novel whole-genome or core-genome gene-by-gene typing schemas and subsequent allele calling in bacterial strains of interest. chewBBACA performs the schema creation and allele calls on complete or draft genomes resulting from de novo assemblers. The chewBBACA software uses Python 3.4 or higher and can run on a laptop or in high performance clusters making it useful for both small laboratories and large reference centers. ChewBBACA is available at https://github.com/B-UMMI/chewBBACA.", "date": "2018-03-01T00:00:00Z", "citationCount": 276, "authors": [ { "name": "Silva M." }, { "name": "Machado M.P." }, { "name": "Silva D.N." }, { "name": "Rossi M." }, { "name": "Moran-Gilad J." }, { "name": "Santos S." }, { "name": "Ramirez M." }, { "name": "Carrico J.A." } ], "journal": "Microbial genomics" } } ], "credit": [], "owner": "EngyNasr", "additionDate": "2025-03-17T15:56:34.552871Z", "lastUpdate": "2025-03-19T14:47:22.843193Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "pyMLST", "description": "A Python Mlst Local Search Tool. The input can be (i) an assembler-generated draft genome, (ii) the direct raw data, or (iii) other genomes stored in the sequence database.", "homepage": "https://github.com/bvalot/pyMLST", "biotoolsID": "pymlst", "biotoolsCURIE": "biotools:pymlst", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3840", "term": "Multilocus sequence typing" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" } ], "operatingSystem": [], "language": [ "Python" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://pymlst.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1099/mgen.0.001126", "pmid": "37966168", "pmcid": "PMC10711306", "type": [], "version": null, "note": null, "metadata": { "title": "Introduction and benchmarking of pyMLST: open-source software for assessing bacterial clonality using core genome MLST", "abstract": "Core genome multilocus sequence typing (cgMLST) has gained in popularity for bacterial typing since whole-genome sequencing (WGS) has become affordable. We introduce here pyMLST, a new complete, stand-alone, free and open source pipeline for cgMLST analysis. pyMLST can create or import a core genome database. For each gene, the first allele is aligned against the bacterial genome of interest using BLAT. Incomplete genes are aligned using MAFT. All data are stored in a SQLite database. pyMLST accepts assembly genomes or raw data (with the option pyMLST-KMA) as input. To evaluate our new tool, we selected three genome collections of major bacterial pathogens (Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus) and compared them with pyMLST, pyMLST-KMA, ChewBBACA, SeqSphere and the variant calling approach. We compared the sensitivity, precision and false-positive rate for each method with those of the variant calling approach. Minimal spanning trees were generated with each type of software to evaluate their interest in the context of a bacterial outbreak. We found that pyMLST-KMA is a convenient screening method to avoid assembling large bacterial collections. Our data showed that pyMLST (free, open source, available in Galaxy and pipeline ready) performed similarly to the commercial SeqSphere and performed better than ChewBBACA and pyMLST-KMA.", "date": "2023-11-01T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Biguenet A." }, { "name": "Bordy A." }, { "name": "Atchon A." }, { "name": "Hocquet D." }, { "name": "Valot B." } ], "journal": "Microbial Genomics" } } ], "credit": [], "owner": "EngyNasr", "additionDate": "2025-03-17T16:13:12.338060Z", "lastUpdate": "2025-03-19T14:40:54.280165Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Phinch", "description": "Data visualization framework aimed at promoting novel explorations of large biological datasets (microbiomes, metagenomes, etc.).", "homepage": "https://phinch.org/", "biotoolsID": "phinch", "biotoolsCURIE": "biotools:phinch", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Desktop application", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1101/009944", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "EngyNasr", "additionDate": "2025-03-17T16:24:23.278579Z", "lastUpdate": "2025-03-19T14:31:46.591915Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "pisad", "description": "Phsaed Intraspecies Sample Anomalies Detection tool", "homepage": "https://github.com/ZhantianXu/PISAD", "biotoolsID": "pisad", "biotoolsCURIE": "biotools:pisad", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [], "operatingSystem": [], "language": [], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "zhantianxu", "additionDate": "2025-03-18T13:10:47.976399Z", "lastUpdate": "2025-03-19T14:27:51.531329Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DDGemb", "description": "Predicting the impact of mutations on protein stability from sequence using protein language models", "homepage": "https://ddgemb.biocomp.unibo.it", "biotoolsID": "ddgemb", "biotoolsCURIE": "biotools:ddgemb", "version": [ "1" ], "otherID": [], "relation": [], "function": [ { "operation": [], "input": [ { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0130", "term": "Protein folding, stability and design" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Italy" ], "elixirCommunity": [ "Rare Diseases", "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "https://ddgemb.biocomp.unibo.it/help/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btaf019", "pmid": "39799516", "pmcid": "PMC11783275", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "DDGemb: predicting protein stability change upon single- and multi-point variations with embeddings and deep learning", "abstract": "Motivation: The knowledge of protein stability upon residue variation is an important step for functional protein design and for understanding how protein variants can promote disease onset. Computational methods are important to complement experimental approaches and allow a fast screening of large datasets of variations. Results: In this work, we present DDGemb, a novel method combining protein language model embeddings and transformer architectures to predict protein ΔΔG upon both single- and multi-point variations. DDGemb has been trained on a high-quality dataset derived from literature and tested on available benchmark datasets of single- and multi-point variations. DDGemb performs at the state of the art in both single- and multi-point variations.", "date": "2025-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Savojardo C." }, { "name": "Manfredi M." }, { "name": "Martelli P.L." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "https://www.biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer", "Developer", "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2025-03-17T14:56:35.753220Z", "lastUpdate": "2025-03-17T15:08:51.796427Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "INPS", "description": "Predicting the impact of mutations on protein stability from sequence", "homepage": "https://inpsmd.biocomp.unibo.it", "biotoolsID": "inps", "biotoolsCURIE": "biotools:inps", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [] } ], "note": "Prediction of the impact of non-synonymous polymorphisms on protein stability", "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0130", "term": "Protein folding, stability and design" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://inpsmd.biocomp.unibo.it/help", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btv291", "pmid": "25957347", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "INPS: Predicting the impact of non-synonymous variations on protein stability from sequence", "abstract": "Motivation: A tool for reliably predicting the impact of variations on protein stability is extremely important for both protein engineering and for understanding the effects of Mendelian and somatic mutations in the genome. Next Generation Sequencing studies are constantly increasing the number of protein sequences. Given the huge disproportion between protein sequences and structures, there is a need for tools suited to annotate the effect of mutations starting from protein sequence without relying on the structure. Here, we describe INPS, a novel approach for annotating the effect of non-synonymous mutations on the protein stability from its sequence. INPS is based on SVM regression and it is trained to predict the thermodynamic free energy change upon single-point variations in protein sequences. Results: We show that INPS performs similarly to the state-of-the-art methods based on protein structure when tested in cross-validation on a non-redundant dataset. INPS performs very well also on a newly generated dataset consisting of a number of variations occurring in the tumor suppressor protein p53. Our results suggest that INPS is a tool suited for computing the effect of non-synonymous polymorphisms on protein stability when the protein structure is not available. We also show that INPS predictions are complementary to those of the state-of-the-art, structure-based method mCSM. When the two methods are combined, the overall prediction on the p53 set scores significantly higher than those of the single methods.", "date": "2015-02-06T00:00:00Z", "citationCount": 111, "authors": [ { "name": "Fariselli P." }, { "name": "Martelli P.L." }, { "name": "Savojardo C." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bioinformatics/btw192", "pmid": "27153629", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "INPS-MD: A web server to predict stability of protein variants from sequence and structure", "abstract": "Motivation: Protein function depends on its structural stability. The effects of single point variations on protein stability can elucidate the molecular mechanisms of human diseases and help in developing new drugs. Recently, we introduced INPS, a method suited to predict the effect of variations on protein stability from protein sequence and whose performance is competitive with the available state-of-the-art tools. Results: In this article, we describe INPS-MD (Impact of Non synonymous variations on Protein Stability-Multi-Dimension), a web server for the prediction of protein stability changes upon single point variation from protein sequence and/or structure. Here, we complement INPS with a new predictor (INPS3D) that exploits features derived from protein 3D structure. INPS3D scores with Pearson's correlation to experimental ΔΔG values of 0.58 in cross validation and of 0.72 on a blind test set. The sequence-based INPS scores slightly lower than the structure-based INPS3D and both on the same blind test sets well compare with the state-of-the-art methods.", "date": "2016-08-15T00:00:00Z", "citationCount": 189, "authors": [ { "name": "Savojardo C." }, { "name": "Fariselli P." }, { "name": "Martelli P.L." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "http://www.biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact" ], "note": null }, { "name": "Piero Fariselli", "email": "piero.fariselli@unito.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2016-05-04T15:36:53Z", "lastUpdate": "2025-03-17T14:54:19.762674Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-ITA-BOLOGNA", "savo" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Raster extraction", "description": "This Python script provides functions to process raster files in chunks and extract values at specified coordinates using multiprocessing. The script is designed to handle large raster datasets efficiently by dividing the workload across multiple CPU cores.", "homepage": "https://github.com/UtrechtUniversity/raster_extraction", "biotoolsID": "raster_extraction", "biotoolsCURIE": "biotools:raster_extraction", "version": [], "otherID": [], "relation": [ { "biotoolsID": "exposome_maps", "type": "uses" } ], "function": [ { "operation": [], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3855", "term": "Environmental sciences" }, { "uri": "http://edamontology.org/topic_3071", "term": "Data management" } ], "operatingSystem": [], "language": [], "license": "Not licensed", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [ { "name": "Lloyd Roga", "email": "l.q.roga@uu.nl", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer", "Maintainer" ], "note": null } ], "owner": "Channel2291", "additionDate": "2025-03-17T14:11:03.252329Z", "lastUpdate": "2025-03-17T14:13:20.238876Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Health Data Nexus", "description": "The Health Data Nexus is T-CAIREM's unique online platform for health data sharing & analytics that emphasizes patient privacy and security, provides transparent and speedy access, and simplifies data discovery and analysis.", "homepage": "https://healthdatanexus.ai/", "biotoolsID": "hdn", "biotoolsCURIE": "biotools:hdn", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3071", "term": "Data management" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" } ], "operatingSystem": [], "language": [], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://tcairem.utoronto.ca/infrastructure-overview", "type": [ "Other" ], "note": null }, { "url": "https://github.com/T-CAIREM/physionet-build", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "rutvikrj26", "additionDate": "2025-03-16T20:15:23.278615Z", "lastUpdate": "2025-03-16T20:26:12.603608Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "emmtyper", "description": "emmtyper is a command line tool for emm-typing of Streptococcus pyogenes using a de novo or complete assembly.\n\nBy default, we use the U.S. Centers for Disease Control and Prevention trimmed emm subtype database, which can be found here (https://www2a.cdc.gov/ncidod/biotech/strepblast.asp). The database is curated by Dr. Velusamy Srinivasan. \n\nInner workings\nThe difficulty in performing M-typing is that there is a single gene of interest (emm), but two other homologue genes (enn and mrp), often referred to as emm-like. The homologue genes may or may not occur in the isolate of interest. When performing emm-typing from an assembly, we can distinguish betweeen one or more clusters of matches on the contigs. The best match for each of the clusters identified is then parsed from the BLAST results. Where possible, we try to distinguish between matches to the emm gene, and matches to one of the emm-like genes.", "homepage": "https://github.com/MDU-PHL/emmtyper", "biotoolsID": "emmtyper", "biotoolsCURIE": "biotools:emmtyper", "version": [ "0.2.0" ], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "maxlcummins", "additionDate": "2025-03-13T03:39:14.949353Z", "lastUpdate": "2025-03-13T03:45:42.872847Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "GTestimate", "description": "GTestimate is a scRNA-seq normalization method. In contrast to other methods it uses the Simple Good-Turing estimator for the per cell relative gene expression estimation.", "homepage": "https://github.com/Martin-Fahrenberger/GTestimate", "biotoolsID": "gtestimate", "biotoolsCURIE": "biotools:gtestimate", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3435", "term": "Standardisation and normalisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3917", "term": "Count matrix" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3112", "term": "Gene expression matrix" }, "format": [] } ], "note": "GTestimate is provided as an R-package containing the GTestimate() function.", "cmd": "GTestimate()" } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Martin-Fahrenberger/GTestimate", "type": [ "Issue tracker", "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/Martin-Fahrenberger/GTestimate", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1101/2024.07.02.601501", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": "2", "note": "preprint version 2", "metadata": null } ], "credit": [], "owner": "martin_fahrenberger", "additionDate": "2025-03-12T15:38:32.218141Z", "lastUpdate": "2025-03-12T15:38:32.221353Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MS2LDA 2.0", "description": "Updated version of MS2LDA for Substructure finding in MS/MS data", "homepage": "https://github.com/vdhooftcompmet/MS2LDA", "biotoolsID": "ms2lda_2.0", "biotoolsCURIE": "biotools:ms2lda_2.0", "version": [ "2.0.0", "2.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3370", "term": "Analytical chemistry" } ], "operatingSystem": [], "language": [ "Python" ], "license": "Freeware", "collectionID": [], "maturity": "Emerging", "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "rosina_to", "additionDate": "2025-03-11T10:18:23.285192Z", "lastUpdate": "2025-03-11T10:18:23.287500Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Arabidopsis Co-expression Tool (ACT)", "description": "The Arabidopsis Coexpression Tool (ACT) is based on the coexpression analysis of 21273 Arabidopsis thaliana genes from gene pair correlation data of 3500 Affymetrix Arabidopsis ATH1 Genome Array Chip microarray samples.", "homepage": "https://www.michalopoulos.net/act/", "biotoolsID": "act", "biotoolsCURIE": "biotools:act", "version": [ "2.6" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2938", "term": "Dendrogram visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1025", "term": "Gene identifier" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3271", "term": "Gene tree" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Greece" ], "elixirCommunity": [ "Plant Sciences" ], "link": [], "download": [], "documentation": [ { "url": "https://www.michalopoulos.net/act2.6/help.php", "type": [ "FAQ" ], "note": null } ], "publication": [ { "doi": "10.3390/genes16030258", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null }, { "doi": "10.1016/j.xpro.2022.101208", "pmid": "35243384", "pmcid": "PMC8885756", "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "Gene coexpression analysis in Arabidopsis thaliana based on public microarray data", "abstract": "Coexpressed genes tend to participate in related biological processes. Gene coexpression analysis allows the discovery of functional gene partners or the assignment of biological roles to genes of unknown function. In this protocol, we describe the steps necessary to create a gene coexpression tree for Arabidopsis thaliana, using publicly available Affymetrix CEL microarray data. Because the computational analysis described here is highly dependent on sample quality, we detail an automatic quality control approach. For complete details on the use and execution of this protocol, please refer to Zogopoulos et al. (2021).", "date": "2022-03-18T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Zogopoulos V.L." }, { "name": "Malatras A." }, { "name": "Michalopoulos I." } ], "journal": "STAR Protocols" } }, { "doi": "10.3390/biology11071019", "pmid": "36101400", "pmcid": "PMC9312353", "type": [ "Review" ], "version": null, "note": null, "metadata": { "title": "Approaches in Gene Coexpression Analysis in Eukaryotes", "abstract": "Gene coexpression analysis constitutes a widely used practice for gene partner identification and gene function prediction, consisting of many intricate procedures. The analysis begins with the collection of primary transcriptomic data and their preprocessing, continues with the calculation of the similarity between genes based on their expression values in the selected sample dataset and results in the construction and visualisation of a gene coexpression network (GCN) and its evaluation using biological term enrichment analysis. As gene coexpression analysis has been studied ex-tensively, we present most parts of the methodology in a clear manner and the reasoning behind the selection of some of the techniques. In this review, we offer a comprehensive and comprehensi-ble account of the steps required for performing a complete gene coexpression analysis in eukary-otic organisms. We comment on the use of RNA‐Seq vs. microarrays, as well as the best practices for GCN construction. Furthermore, we recount the most popular webtools and standalone applications performing gene coexpression analysis, with details on their methods, features and outputs.", "date": "2022-07-01T00:00:00Z", "citationCount": 9, "authors": [ { "name": "Zogopoulos V.L." }, { "name": "Saxami G." }, { "name": "Malatras A." }, { "name": "Papadopoulos K." }, { "name": "Tsotra I." }, { "name": "Iconomidou V.A." }, { "name": "Michalopoulos I." } ], "journal": "Biology" } }, { "doi": "10.1093/nar/gkl204", "pmid": "16845059", "pmcid": "PMC1538833", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Arabidopsis Co-expression Tool (ACT): Web server tools for microarray-based gene expression analysis", "abstract": "The Arabidopsis Co-expression Tool, ACT, ranks the genes across a large microarray dataset according to how closely their expression follows the expression of a query gene. A database stores pre-calculated co-expression results for ∼21 800 genes based on data from over 300 arrays. These results can be corroborated by calculation of co-expression results for user-defined sub-sets of arrays or experiments from the NASC/GARNet array dataset. Clique Finder (CF) identifies groups of genes which are consistently co-expressed with each other across a user-defined co-expression list. The parameters can be altered easily to adjust cluster size and the output examined for optimal inclusion of genes with known biological roles. Alternatively, a Scatter Plot tool displays the correlation coefficients for all genes against two user-selected queries on a scatter plot which can be useful for visual identification of clusters of genes with similar r-values. User-input groups of genes can be highlighted on the scatter plots. Inclusion of genes with known biology in sets of genes identified using CF and Scatter Plot tools allows inferences to be made about the roles of the other genes in the set and both tools can therefore be used to generate short lists of genes for further characterization. ACT is freely available at www.Arabidopsis.leeds.ac.uk/ACT. © The Author 2006. Published by Oxford University Press. All rights reserved.", "date": "2006-07-01T00:00:00Z", "citationCount": 130, "authors": [ { "name": "Manfield I.W." }, { "name": "Jen C.-H." }, { "name": "Pinney J.W." }, { "name": "Michalopoulos I." }, { "name": "Bradford J.R." }, { "name": "Gilmartin P.M." }, { "name": "Westhead D.R." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1111/j.1365-313x.2006.02681.x", "pmid": "16623895", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "The Arabidopsis co-expression tool (ACT): A WWW-based tool and database for microarray-based gene expression analysis", "abstract": "We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (ACT), based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression patterns are correlated across selected experiments or the complete data set. Results are accompanied by estimates of the statistical significance of the correlation relationships, expressed as probability (P) and expectation (E) values. Additionally, highly ranked genes on a correlation list can be examined using the novel CLIQUE FINDER tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots, and dissection into cliques of co-regulated genes. We illustrate the applications of the software by analysing genes encoding functionally related proteins, as well as pathways involved in plant responses to environmental stimuli. These analyses demonstrate novel biological relationships underlying the observed gene co-expression patterns. To demonstrate the ability of the software to develop testable hypotheses on gene function within a defined biological process we have used the example of cell wall biosynthesis genes. The resource is freely available at http://www.arabidopsis.leeds.ac.uk/ACT/. © 2006 The Authors.", "date": "2006-04-01T00:00:00Z", "citationCount": 65, "authors": [ { "name": "Jen C.-H." }, { "name": "Manfield I.W." }, { "name": "Michalopoulos I." }, { "name": "Pinney J.W." }, { "name": "Willats W.G.T." }, { "name": "Gilmartin P.M." }, { "name": "Westhead D.R." } ], "journal": "Plant Journal" } }, { "doi": "10.1016/j.isci.2021.102848", "pmid": "34381973", "pmcid": "PMC8334378", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Arabidopsis Coexpression Tool: a tool for gene coexpression analysis in Arabidopsis thaliana", "abstract": "Gene coexpression analysis refers to the discovery of sets of genes which exhibit similar expression patterns across multiple transcriptomic data sets, such as microarray experiment data of public repositories. Arabidopsis Coexpression Tool (ACT), a gene coexpression analysis web tool for Arabidopsis thaliana, identifies genes which are correlated to a driver gene. Primary microarray data from ATH1 Affymetrix platform were processed with Single-Channel Array Normalization algorithm and combined to produce a coexpression tree which contains ∼21,000 A. thaliana genes. ACT was developed to present subclades of coexpressed genes, as well as to perform gene set enrichment analysis, being unique in revealing enriched transcription factors targeting coexpressed genes. ACT offers a simple and user-friendly interface producing working hypotheses which can be experimentally verified for the discovery of gene partnership, pathway membership, and transcriptional regulation. ACT analyses have been successful in identifying not only genes with coordinated ubiquitous expressions but also genes with tissue-specific expressions.", "date": "2021-08-20T00:00:00Z", "citationCount": 14, "authors": [ { "name": "Zogopoulos V.L." }, { "name": "Saxami G." }, { "name": "Malatras A." }, { "name": "Angelopoulou A." }, { "name": "Jen C.-H." }, { "name": "Duddy W.J." }, { "name": "Daras G." }, { "name": "Hatzopoulos P." }, { "name": "Westhead D.R." }, { "name": "Michalopoulos I." } ], "journal": "iScience" } } ], "credit": [ { "name": "David R Westhead", "email": "D.R.Westhead@leeds.ac.uk", "url": "https://biologicalsciences.leeds.ac.uk/molecular-and-cellular-biology/staff/154/professor-david-r-westhead", "orcidid": "https://orcid.org/0000-0002-0519-3820", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Ioannis Michalopoulos", "email": "imichalop@bioacademy.gr", "url": "https://www.michalopoulos.net/", "orcidid": "https://orcid.org/0000-0001-8991-8712", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "imichalop@bioacademy.gr", "additionDate": "2017-02-10T14:14:47Z", "lastUpdate": "2025-03-10T11:30:02.403040Z", "editPermission": { "type": "private", "authors": [ "imichalop@bioacademy.gr" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "NetworkDataCompanion", "description": "An R library of utilities for performing analyses on TCGA and GTEx data using the Network Zoo.", "homepage": "https://github.com/QuackenbushLab/NetworkDataCompanion", "biotoolsID": "NetworkDataCompanion", "biotoolsCURIE": "biotools:NetworkDataCompanion", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1101/2024.11.05.622163", "pmid": "39574772", "pmcid": "PMC11580957", "type": [ "Other" ], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "kshutta", "additionDate": "2025-03-05T18:39:41.473327Z", "lastUpdate": "2025-03-05T18:45:38.640013Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PEP-FOLD4", "description": "PEP-FOLD4 is a fast and accurate structure prediction tool for peptides of up to 40 amino acids in aqueous solutions. Unlike many machine-learning approaches (e.g., AlphaFold2, TrRosetta, RaptorX), it integrates the Debye-Hückel formalism for charged side-chain interactions with a Mie potential for intramolecular forces. 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Adding the Debye-Hueckel formalism for charged-charged side chain interactions to a Mie formalism for all intramolecular (backbone and side chain) interactions, PEP-FOLD4, based on a coarse-grained representation of the peptides, performs as well as machine-learning methods on well-structured peptides, but displays significant improvements for poly-charged peptides. PEP-FOLD4 is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD4. 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The MORE method applies MLRs or PLS to model a target omic expression as a function of experimental variables, such as diseases or treatments, and the potential regulators of that given target feature. 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When the paper is published the link wil be updated.", "metadata": null } ], "credit": [ { "name": "Maider Aguerralde Martin", "email": "magumar2@posgrado.upv.es", "url": null, "orcidid": "https://orcid.org/0000-0001-9266-8689", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer" ], "note": null } ], "owner": "biostatomics1", "additionDate": "2025-03-03T11:35:43.315630Z", "lastUpdate": "2025-03-04T15:19:11.815695Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MultiPower", "description": "The MultiPower R method performs statistical power studies for multi-omics experiments, and is designed to assist users in experimental design as well as in the evaluation of already-generated multi-omics datasets.", "homepage": "https://github.com/ConesaLab/MultiPower", "biotoolsID": "multipower", "biotoolsCURIE": "biotools:multipower", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_4031", "term": "Power test" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_4021", "term": "Multiomics" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "GPL-2.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/ConesaLab/MultiPower", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/ConesaLab/MultiPower/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/ConesaLab/MultiPower/blob/master/MultiPowerUsersGuide_v2.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1038/s41467-020-16937-8", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Harmonization of quality metrics and power calculation in multi-omic studies", "abstract": "Multi-omic studies combine measurements at different molecular levels to build comprehensive models of cellular systems. The success of a multi-omic data analysis strategy depends largely on the adoption of adequate experimental designs, and on the quality of the measurements provided by the different omic platforms. However, the field lacks a comparative description of performance parameters across omic technologies and a formulation for experimental design in multi-omic data scenarios. Here, we propose a set of harmonized Figures of Merit (FoM) as quality descriptors applicable to different omic data types. Employing this information, we formulate the MultiPower method to estimate and assess the optimal sample size in a multi-omics experiment. MultiPower supports different experimental settings, data types and sample sizes, and includes graphical for experimental design decision-making. MultiPower is complemented with MultiML, an algorithm to estimate sample size for machine learning classification problems based on multi-omic data.", "date": "2020-12-01T00:00:00Z", "citationCount": 54, "authors": [ { "name": "Tarazona S." }, { "name": "Balzano-Nogueira L." }, { "name": "Gomez-Cabrero D." }, { "name": "Schmidt A." }, { "name": "Imhof A." }, { "name": "Hankemeier T." }, { "name": "Tegner J." }, { "name": "Westerhuis J.A." }, { "name": "Conesa A." } ], "journal": "Nature Communications" } } ], "credit": [ { "name": "Sonia Tarazona", "email": "sotacam@eio.upv.es", "url": null, "orcidid": "https://orcid.org/0000-0001-5346-1407", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer" ], "note": null } ], "owner": "biostatomics1", "additionDate": "2025-03-03T15:06:10.867996Z", "lastUpdate": "2025-03-04T15:16:47.048391Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MOSim", "description": "MOSim (Multi-Omics Simulation) package simulates multi-omic experiments that mimic regulatory mechanisms within the cell, allowing flexible experimental design including time course and multiple groups.", "homepage": "https://bioconductor.org/packages/release/bioc/html/MOSim.html", "biotoolsID": "mosim", "biotoolsCURIE": "biotools:mosim", "version": [ "2.2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_4021", "term": "Multiomics" }, { "uri": "http://edamontology.org/topic_3524", "term": "Simulation experiment" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/ConesaLab/MOSim", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/ConesaLab/MOSim/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1101/421834", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": "This is a preprint accesible at bioRxiv. When the paper is published it will be updated", "metadata": null } ], "credit": [ { "name": "Sonia Tarazona", "email": "sotacam@eio.upv.es", "url": null, "orcidid": "https://orcid.org/0000-0001-5346-1407", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer" ], "note": null } ], "owner": "biostatomics1", "additionDate": "2025-03-03T13:46:56.613465Z", "lastUpdate": "2025-03-04T15:12:34.696650Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Attune", "description": "Attune offers a versatile framework for integrating gene expression and chromatin accessibility, enabling the inference of regulatory mechanisms and the prediction of gene expression from cross-modal data.", "homepage": "https://github.com/melobio/Attune", "biotoolsID": "attune", "biotoolsCURIE": "biotools:attune", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "admin", "additionDate": "2025-03-03T08:03:47.168169Z", "lastUpdate": "2025-03-03T08:08:06.816312Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "compareMS2", "description": "compareMS2 is a tool for comparing sets of (tandem) mass spectra for clustering samples, molecular phylogenetics, identification of biological species or tissues, and quality control. compareMS2 currently consumes Mascot Generic Format, or MGF, and produces output in a variety of common image and distance matrix formats.", "homepage": "https://github.com/524D/compareMS2", "biotoolsID": "comparems2", "biotoolsCURIE": "biotools:comparems2", "version": [ "1.0", "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2424", "term": "Comparison" }, { "uri": "http://edamontology.org/operation_0567", "term": "Phylogenetic tree visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3651", "term": "MGF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3272", "term": "Species tree" }, "format": [ { "uri": "http://edamontology.org/format_3603", "term": "PNG" }, { "uri": "http://edamontology.org/format_3604", "term": "SVG" } ] }, { "data": { "uri": "http://edamontology.org/data_2855", "term": "Distance matrix" }, "format": [ { "uri": "http://edamontology.org/format_1991", "term": "mega" }, { "uri": "http://edamontology.org/format_1912", "term": "Nexus format" }, { "uri": "http://edamontology.org/format_1910", "term": "newick" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0084", "term": "Phylogeny" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C", "JavaScript" ], "license": "MIT", "collectionID": [ "ms-utils", "Proteomics" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Netherlands" ], "elixirCommunity": [ "Proteomics" ], "link": [ { "url": "https://github.com/524D/compareMS2", "type": [ "Repository" ], "note": null }, { "url": "https://www.ms-utils.org/compareMS2.html", "type": [ "Software catalogue" ], "note": null }, { "url": "https://research-software-directory.org/software/comparems2", "type": [ "Software catalogue" ], "note": null } ], "download": [ { "url": "http://www.ms-utils.org/compareMS2.c", "type": "Source code", "note": null, "version": "1.0" }, { "url": "http://www.ms-utils.org/compareMS2.html", "type": "Binaries", "note": null, "version": "1.0" }, { "url": "http://www.ms-utils.org/compareMS2.c", "type": "Source code", "note": null, "version": "1.0" }, { "url": "https://github.com/524D/compareMS2/tree/main/src", "type": "Source code", "note": null, "version": "2.0" }, { "url": "https://github.com/524D/compareMS2/tree/main", "type": "Binaries", "note": null, "version": "2.0" } ], "documentation": [ { "url": "http://www.ms-utils.org/compareMS2.html", "type": [ "General", "Command-line options" ], "note": null }, { "url": "https://github.com/524D/compareMS2", "type": [ "General", "User manual", "Command-line options", "Installation instructions" ], "note": null } ], "publication": [ { "doi": "10.1002/rcm.6162", "pmid": "22368051", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Molecular phylogenetics by direct comparison of tandem mass spectra", "abstract": "Rationale: Molecular phylogenetics is the study of evolution and relatedness of organisms or genes. Mass spectrometry is used routinely for bacterial identification and has also been used for phylogenetic analysis, for instance from bone material. Unfortunately, only a small fraction of the acquired tandem mass spectra allow direct interpretation. Methods: We describe a new algorithm and software for molecular phylogenetics using pairwise comparisons of tandem mass spectra from enzymatically digested proteins. The spectra need not be annotated and all acquired data is used in the analysis. To demonstrate the method, we analyzed tryptic digests of sera from four great apes and two other primates. Results: The distribution of spectra dot products for thousands of tandem mass spectra collected from two samples provides a measure on the fraction of shared peptides between the two samples. When inverted, this becomes a distance metric. By pairwise comparison between species and averaging over four individuals per species, it was possible to reconstruct the unique correct phylogenetic tree for the great apes and other primates. Conclusions: The new method described here has several attractive features compared with existing methods, among them simplicity, the unbiased use of all acquired data rather than a small subset of spectra, and the potential use of heavily degraded proteins or proteins with a priori unknown modifications. © 2012 John Wiley & Sons, Ltd.", "date": "2012-04-15T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Palmblad M." }, { "name": "Deelder A.M." } ], "journal": "Rapid Communications in Mass Spectrometry" } }, { "doi": "10.1021/acs.jproteome.2c00457", "pmid": "36173614", "pmcid": "PMC9903320", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry Datasets", "abstract": "It has long been known that biological species can be identified from mass spectrometry data alone. Ten years ago, we described a method and software tool, compareMS2, for calculating a distance between sets of tandem mass spectra, as routinely collected in proteomics. This method has seen use in species identification and mixture characterization in food and feed products, as well as other applications. Here, we present the first major update of this software, including a new metric, a graphical user interface and additional functionality. The data have been deposited to ProteomeXchange with dataset identifier PXD034932.", "date": "2023-02-03T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Marissen R." }, { "name": "Varunjikar M.S." }, { "name": "Laros J.F.J." }, { "name": "Rasinger J.D." }, { "name": "Neely B.A." }, { "name": "Palmblad M." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1021/acs.jproteome.1c00528", "pmid": "34523928", "pmcid": "PMC8491155", "type": [ "Review" ], "version": "2.0", "note": null, "metadata": { "title": "Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics Experiments in the Light of Proteomics", "abstract": "Science is full of overlooked and undervalued research waiting to be rediscovered. Proteomics is no exception. In this perspective, we follow the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing tryptic peptides across animal species. This pioneering work directly led to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics. In the decades following, proteins continued to provide essential clues on evolutionary history. While technology has continued to improve, contemporary proteomics has strayed from this larger biological context, rarely comparing species or asking how protein structure, function, and interactions have evolved. Here we recombine proteomics with molecular phylogenetics, highlighting the value of framing proteomic results in a larger biological context and how almost forgotten research, though technologically surpassed, can still generate new ideas and illuminate our work from a different perspective. Though it is infeasible to read all research published on a large topic, looking up older papers can be surprisingly rewarding when rediscovering a \"gem\"at the end of a long citation chain, aided by digital collections and perpetually helpful librarians. Proper literature study reduces unnecessary repetition and allows research to be more insightful and impactful by truly standing on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/) as dataset MSV000087993.", "date": "2021-10-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Neely B.A." }, { "name": "Palmblad M." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "lumc.nl", "email": null, "url": "https://www.lumc.nl", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Support" ], "note": null }, { "name": "Magnus Palmblad", "email": "magnus.palmblad@gmail.com", "url": "https://github.com/magnuspalmblad", "orcidid": "http://orcid.org/0000-0002-5865-8994", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact", "Documentor" ], "note": null }, { "name": "Rob Marissen", "email": null, "url": "https://github.com/524D", "orcidid": "https://orcid.org/0000-0002-1220-9173", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2016-04-15T11:52:42Z", "lastUpdate": "2025-02-28T16:15:29.918624Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "hictk", "description": "Blazing fast toolkit to work with .hic and .cool files", "homepage": "https://github.com/paulsengroup/hictk", "biotoolsID": "hictk", "biotoolsCURIE": "biotools:hictk", "version": [ "0.0.1", "0.0.2", "0.0.3", "0.0.4", "0.0.5", "0.0.6", "0.0.7", "0.0.8", "0.0.9", "0.0.10", "0.0.11", "0.0.12", "1.0.0", "2.0.0", "2.0.1", "2.0.2" ], "otherID": [], "relation": [ { "biotoolsID": "hictkpy", "type": "usedBy" }, { "biotoolsID": "hictkr", "type": "usedBy" } ], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/paulsengroup/hictk", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/paulsengroup/hictk/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/paulsengroup/hictk/discussions", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://github.com/paulsengroup/hictk/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://anaconda.org/bioconda/hictk", "type": "Binaries", "note": null, "version": null }, { "url": "https://github.com/paulsengroup/hictk/pkgs/container/hictk", "type": "Container file", "note": null, "version": null } ], "documentation": [ { "url": "https://hictk.readthedocs.io/en/stable/index.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btae408", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "hictk: blazing fast toolkit to work with. hic and. cool files", "abstract": "Motivation: Hi-C is gaining prominence as a method for mapping genome organization. With declining sequencing costs and a growing demand for higher-resolution data, efficient tools for processing Hi-C datasets at different resolutions are crucial. Over the past decade, the. hic and Cooler file formats have become the de-facto standard to store interaction matrices produced by Hi-C experiments in binary format. Interoperability issues make it unnecessarily difficult to convert between the two formats and to develop applications that can process each format natively. Results: We developed hictk, a toolkit that can transparently operate on. hic and. cool files with excellent performance. The toolkit is written in C++ and consists of a C++ library with Python and R bindings as well as CLI tools to perform common operations directly from the shell, including converting between. hic and. mcool formats. We benchmark the performance of hictk and compare it with other popular tools and libraries. We conclude that hictk significantly outperforms existing tools while providing the flexibility of natively working with both file formats without code duplication.", "date": "2024-07-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Rossini R." }, { "name": "Paulsen J." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "robomics", "additionDate": "2024-02-02T14:42:46.030561Z", "lastUpdate": "2025-02-27T17:22:32.508665Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MetIDfyR", "description": "Open-Source R Package to Decipher Small-Molecule Drugs Metabolism Through High Resolution Mass Spectrometry.\n\nMetIDfyR is an open-source, cross-platform and versatile R script to predict and detect metabolites in mass spectrometry data (mzML) based on the raw formula of the drug of interest.", "homepage": "https://github.com/agnesbrnb/MetIDfyR", "biotoolsID": "metidfyr", "biotoolsCURIE": "biotools:metidfyr", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3803", "term": "Natural product identification" }, { "uri": "http://edamontology.org/operation_3454", "term": "Phasing" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3244", "term": "mzML" } ] }, { "data": { "uri": "http://edamontology.org/data_0846", "term": "Chemical formula" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [ { "uri": "http://edamontology.org/format_3604", "term": "SVG" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_3375", "term": "Drug metabolism" }, { "uri": "http://edamontology.org/topic_3370", "term": "Analytical chemistry" } ], "operatingSystem": [], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/agnesbrnb/MetIDfyR", "type": [ "Quick start guide", "Installation instructions", "Citation instructions" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.analchem.0c02281", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "MetIDfyR: An Open-Source R Package to Decipher Small-Molecule Drug Metabolism through High-Resolution Mass Spectrometry", "abstract": "With recent advances in analytical chemistry, liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS) has become an essential tool for metabolite discovery and detection. Even if most of the common drug transformations have already been extensively described, manual search of drug metabolites in LC-HRMS/MS datasets is still a common practice in toxicology laboratories, complicating metabolite discovery. Furthermore, the availability of free open-source software for metabolite discovery is still limited. In this article, we present MetIDfyR, an open-source and cross-platform R package for in silico drug phase I/II biotransformation prediction and mass-spectrometric data mining. MetIDfyR has proven its efficacy for advanced metabolite identification in semi-complex and complex mixtures in in vitro or in vivo drug studies and is freely available at github.com/agnesblch/MetIDfyR.", "date": "2020-10-06T00:00:00Z", "citationCount": 10, "authors": [ { "name": "Delcourt V." }, { "name": "Barnabe A." }, { "name": "Loup B." }, { "name": "Garcia P." }, { "name": "Andre F." }, { "name": "Chabot B." }, { "name": "Trevisiol S." }, { "name": "Moulard Y." }, { "name": "Popot M.-A." }, { "name": "Bailly-Chouriberry L." } ], "journal": "Analytical Chemistry" } } ], "credit": [], "owner": "agnesbarnabe", "additionDate": "2021-01-18T09:08:27Z", "lastUpdate": "2025-02-27T15:46:01.807140Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "GreedyFHist", "description": "GreedyFHist - Registration of stained histology images.", "homepage": "https://github.com/mwess/GreedyFHist", "biotoolsID": "greedyfhist", "biotoolsCURIE": "biotools:greedyfhist", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3443", "term": "Image analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/mwess/GreedyFHist", "type": "Source code", "note": null, "version": null }, { "url": "https://hub.docker.com/r/mwess89/greedyfhist", "type": "Other", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/mwess/GreedyFHist", "type": [ "Quick start guide", "Installation instructions" ], "note": null }, { "url": "https://greedyfhist.readthedocs.io/en/latest/", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1101/2024.06.11.598306", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "mwess", "additionDate": "2025-02-27T08:06:39.387454Z", "lastUpdate": "2025-02-27T08:08:15.778610Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null } ] }