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{ "count": 3402, "next": "?page=2", "previous": null, "list": [ { "name": "Pfeature", "description": "Pfeature is a web server for computing wide range of protein and peptides features from their amino acid sequence. Following are main menus for computing features; i) Composition-based features, ii) Binary profile of sequences, iii) evolutionary information based features, iv) structural descriptors, v) pattern based descriptors, and vi) model building, for a group of protein/peptide sequences. Additionally, users will also be able to generate these features for sub-parts of protein/peptide sequences. Pfeature be helpful to annotate structure, function and therapeutic properties of proteins/peptides.", "homepage": "https://webs.iiitd.edu.in/raghava/pfeature/", "biotoolsID": "pfeature", "biotoolsCURIE": "biotools:pfeature", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Web service", "Command-line tool", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_0605", "term": "Informatics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python", "PHP" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://webs.iiitd.edu.in/raghava/pfeature/Pfeature_Manual.pdf", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://webs.iiitd.edu.in/raghava/pfeature/stand.php", "type": "Downloads page", "note": null, "version": null }, { "url": "https://github.com/raghavagps/pfeature", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://webs.iiitd.edu.in/raghava/pfeature/Pfeature_Manual.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1089/cmb.2022.0241", "pmid": "36251780", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Pfeature: A Tool for Computing Wide Range of Protein Features and Building Prediction Models", "abstract": "In the last three decades, a wide range of protein features have been discovered to annotate a protein. Numerous attempts have been made to integrate these features in a software package/platform so that the user may compute a wide range of features from a single source. To complement the existing methods, we developed a method, Pfeature, for computing a wide range of protein features. Pfeature allows to compute more than 200,000 features required for predicting the overall function of a protein, residue-level annotation of a protein, and function of chemically modified peptides. It has six major modules, namely, composition, binary profiles, evolutionary information, structural features, patterns, and model building. Composition module facilitates to compute most of the existing compositional features, plus novel features. The binary profile of amino acid sequences allows to compute the fraction of each type of residue as well as its position. The evolutionary information module allows to compute evolutionary information of a protein in the form of a position-specific scoring matrix profile generated using Position-Specific Iterative Basic Local Alignment Search Tool (PSI-BLAST); fit for annotation of a protein and its residues. A structural module was developed for computing of structural features/descriptors from a tertiary structure of a protein. These features are suitable to predict the therapeutic potential of a protein containing non-natural or chemically modified residues. The model-building module allows to implement various machine learning techniques for developing classification and regression models as well as feature selection. Pfeature also allows the generation of overlapping patterns and features from a protein. A user-friendly Pfeature is available as a web server python library and stand-alone package.", "date": "2023-02-01T00:00:00Z", "citationCount": 14, "authors": [ { "name": "Pande A." }, { "name": "Patiyal S." }, { "name": "Lathwal A." }, { "name": "Arora C." }, { "name": "Kaur D." }, { "name": "Dhall A." }, { "name": "Mishra G." }, { "name": "Kaur H." }, { "name": "Sharma N." }, { "name": "Jain S." }, { "name": "Usmani S.S." }, { "name": "Agrawal P." }, { "name": "Kumar R." }, { "name": "Kumar V." }, { "name": "Raghava G.P.S." } ], "journal": "Journal of Computational Biology" } } ], "credit": [ { "name": "Gajendra P.S. Raghava", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-8902-2876", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Vinod Kumar", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Akshara Pande", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Sumeet Patiyal", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "community": null, "owner": "raghavagps", "additionDate": "2022-10-12T11:22:45.603931Z", "lastUpdate": "2024-07-24T10:45:03.028526Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Stitch", "description": "Stitch is a software tool that performs template-based assembly of proteomics short reads for de novo antibody sequencing and repertoire profiling.", "homepage": "https://github.com/snijderlab/stitch", "biotoolsID": "stitch-snijderlab", "biotoolsCURIE": "biotools:stitch-snijderlab", "version": [ "1.5.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0310", "term": "Sequence assembly" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1233", "term": "Sequence set (protein)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" }, { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_1477", "term": "mmCIF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1233", "term": "Sequence set (protein)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": "Assembles de novo peptide sequences against known antibody gene segments to reconstruct complete antibody sequences.\nFor batch file (job file) specifications, see https://github.com/snijderlab/stitch/blob/master/BatchFiles.md.\nOptions:\n--expect - The expected result(s) of the run as the final sequence(s) by separated commas, used for automated testing;\n--open - Open the HTML report (if available) automatically in the browser;\n--live - Prepare the HTML report for use with VS Code Live Server on the given port, -1 turns it off;\n--quiet - Turns off any output on the command line in normal operation.", "cmd": "stitch run [OPTIONS] <batchfile>" }, { "operation": [ { "uri": "http://edamontology.org/operation_2425", "term": "Optimisation and refinement" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": "Utilizes a mass-based alignment algorithm to handle mass coincidence errors and differentiates between isoleucine and leucine residues using secondary fragments. Generates two CSV files: one with refined reads and another with positional information.\nOptions:\n--output - The filename of the refined reads, the extension will be added automatically;\n--peaks-version - The version of the Peaks file format to use.", "cmd": "stitch refine [OPTIONS] <input> <raw-data-dir>" }, { "operation": [ { "uri": "http://edamontology.org/operation_1812", "term": "Parsing" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1233", "term": "Sequence set (protein)" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1233", "term": "Sequence set (protein)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": "Parses the sequences from an IMGT HTML file and creates annotated fasta files (also cleans data).\nOptions:\n--output - The output file name, if missing will overwrite the input file.", "cmd": "stitch annotate [OPTIONS] <input>" }, { "operation": [ { "uri": "http://edamontology.org/operation_2409", "term": "Data handling" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1233", "term": "Sequence set (protein)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1233", "term": "Sequence set (protein)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": "Removes duplicates and incomplete sequences from fasta. \nOptions: \n--output - The output file name, if missing will overwrite the input file.", "cmd": "stitch clean [OPTIONS] <input>" } ], "toolType": [ "Command-line tool" ], "topic": [], "operatingSystem": [ "Windows", "Linux", "Mac" ], "language": [ "C#" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/snijderlab/stitch", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/snijderlab/stitch/releases/tag/v1.5.0", "type": "Downloads page", "note": null, "version": "1.5.0" } ], "documentation": [], "publication": [ { "doi": "10.1021/acs.jproteome.4c00188", "pmid": "38932690", "pmcid": null, "type": [], "version": "1.5.0", "note": null, "metadata": { "title": "A Handle on Mass Coincidence Errors in De Novo Sequencing of Antibodies by Bottom-up Proteomics", "abstract": "Antibody sequences can be determined at 99% accuracy directly from the polypeptide product by using bottom-up proteomics techniques. Sequencing accuracy at the peptide level is limited by the isobaric residues leucine and isoleucine, incomplete fragmentation spectra in which the order of two or more residues remains ambiguous due to lacking fragment ions for the intermediate positions, and isobaric combinations of amino acids, of potentially different lengths, for example, GG = N and GA = Q. Here, we present several updates to Stitch (v1.5), which performs template-based assembly of de novo peptides to reconstruct antibody sequences. This version introduces a mass-based alignment algorithm that explicitly accounts for mass coincidence errors. In addition, it incorporates a postprocessing procedure to assign I/L residues based on secondary fragments (satellite ions, i.e., w-ions). Moreover, evidence for sequence assignments can now be directly evaluated with the addition of an integrated spectrum viewer. Lastly, input data from a wider selection of de novo peptide sequencing algorithms are allowed, now including Casanovo, PEAKS, Novor.Cloud, pNovo, and MaxNovo, in addition to flat text and FASTA. Combined, these changes make Stitch compatible with a larger range of data processing pipelines and improve its tolerance to peptide-level sequencing errors.", "date": "2024-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Schulte D." }, { "name": "Snijder J." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Douwe Schulte", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-0594-0993", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "Software Engineer" }, { "name": "Joost Snijder", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-9310-8226", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": "Principal Investigator" }, { "name": "Bastiaan de Graaf", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": "Code Reviews" }, { "name": "Wei Wei Peng", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": "Testing and Analysis" }, { "name": "Biomolecular Mass Spectrometry and Proteomics", "email": null, "url": "https://www.uu.nl/en/research/biomolecular-mass-spectrometry-and-proteomics", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [], "note": "Group at Utrecht University" } ], "community": null, "owner": "thatmariia", "additionDate": "2024-07-17T13:27:56.256529Z", "lastUpdate": "2024-07-18T14:56:47.152424Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DISGENET", "description": "DISGENET is a comprehensive knowledge database integrating and standardizing information on disease-associated genes and variants. It covers the full spectrum of human diseases as well as normal and abnormal traits, including adverse events of drugs. Due to the adherence to FAIR data principles, DISGENET is an interoperable resource supporting a variety of applications in genomic medicine and drug R&D.\n\nDISGENET simplifies the process of accessing genetic evidence for diseases and therefore can streamline the incorporation of this type of evidence in research, drug R&D and precision medicine applications.\n\nDISGENET is available for free for academic users. License fees are applicable for the commercial use of DISGENET. Learn more here https://www.disgenet.com/plans\n\nDISGENET is the new evolution of the community-recognized DisGeNET platform, cited by over 6000 publications and one of the ELIXIR Recommended Interoperability Resources.", "homepage": "http://www.disgenet.com/", "biotoolsID": "disgenet", "biotoolsCURIE": "biotools:disgenet", "version": [ "Database version 24.2", "disgenet2r R package Version: 1.1.9", "DISGENET Cytoscape App Version 8.0.0" ], "otherID": [], "relation": [ { "biotoolsID": "uniprot", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_3226", "term": "Variant prioritisation" }, { "uri": "http://edamontology.org/operation_3083", "term": "Pathway or network visualisation" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_3925", "term": "Network visualisation" }, { "uri": "http://edamontology.org/operation_0306", "term": "Text mining" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3021", "term": "UniProt accession" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1106", "term": "dbSNP ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2858", "term": "Ontology concept" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1025", "term": "Gene identifier" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Plug-in", "Web API", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_3344", "term": "Biomedical science" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_0218", "term": "Natural language processing" }, { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3366", "term": "Data integration and warehousing" }, { "uri": "http://edamontology.org/topic_3345", "term": "Data identity and mapping" }, { "uri": "http://edamontology.org/topic_3342", "term": "Translational medicine" }, { "uri": "http://edamontology.org/topic_0634", "term": "Pathology" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "Proprietary", "collectionID": [ "Drug Research and Development", "Rare Disease", "COVID-19", "Complex Disease", "Mendelian Disease", "ELIXIR-ES", "RIS3CAT VEIS", "TransQST", "IMPaCT-Data" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access (with restrictions)", "elixirPlatform": [ "Interoperability" ], "elixirNode": [ "Spain" ], "elixirCommunity": [], "link": [ { "url": "http://www.disgenet.com/", "type": [ "Repository" ], "note": null }, { "url": "https://apps.cytoscape.org/apps/disgenetapp", "type": [ "Software catalogue" ], "note": null }, { "url": "https://www.linkedin.com/showcase/disgenet/", "type": [ "Social media" ], "note": null }, { "url": "https://gitlab.com/medbio/disgenet2r", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://gitlab.com/medbio/disgenet2r", "type": "Software package", "note": "disgenet2r R package", "version": null }, { "url": "https://apps.cytoscape.org/apps/disgenetapp", "type": "Software package", "note": "DISGENET Cytoscape App", "version": null }, { "url": "https://www.disgenet.com/Tools#console", "type": "API specification", "note": "DISGENET REST API", "version": null } ], "documentation": [ { "url": "https://www.disgenet.com/About", "type": [ "General" ], "note": null }, { "url": "https://www.disgenet.com/Tools#console", "type": [ "API documentation" ], "note": null }, { "url": "https://www.disgenet.com/FAQ", "type": [ "FAQ" ], "note": null } ], "publication": [ { "doi": "10.1093/database/bav028", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "DisGeNET: A discovery platform for the dynamical exploration of human diseases and their genes", "abstract": "DisGeNET is a comprehensive discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET contains over 380 000 associations between >16 000 genes and 13 000 diseases, which makes it one of the largest repositories currently available of its kind. DisGeNET integrates expert-curated databases with text-mined data, covers information on Mendelian and complex diseases, and includes data from animal disease models. It features a score based on the supporting evidence to prioritize gene-disease associations. It is an open access resource available through a web interface, a Cytoscape plugin and as a Semantic Web resource. The web interface supports user-friendly data exploration and navigation. DisGeNET data can also be analysed via the DisGeNET Cytoscape plugin, and enriched with the annotations of other plugins of this popular network analysis software suite. Finally, the information contained in DisGeNET can be expanded and complemented using Semantic Web technologies and linked to a variety of resources already present in the Linked Data cloud. Hence, DisGeNET offers one of the most comprehensive collections of human gene-disease associations and a valuable set of tools for investigating the molecular mechanisms underlying diseases of genetic origin, designed to fulfill the needs of different user profiles, including bioinformaticians, biologists and health-care practitioners.", "date": "2015-01-01T00:00:00Z", "citationCount": 761, "authors": [ { "name": "Pinero J." }, { "name": "Queralt-Rosinach N." }, { "name": "Bravo A." }, { "name": "Deu-Pons J." }, { "name": "Bauer-Mehren A." }, { "name": "Baron M." }, { "name": "Sanz F." }, { "name": "Furlong L.I." } ], "journal": "Database" } }, { "doi": "10.1093/nar/gkw943", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "DisGeNET: A comprehensive platform integrating information on human disease-associated genes and variants", "abstract": "The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.", "date": "2017-01-01T00:00:00Z", "citationCount": 1604, "authors": [ { "name": "Pinero J." }, { "name": "Bravo A." }, { "name": "Queralt-Rosinach N." }, { "name": "Gutierrez-Sacristan A." }, { "name": "Deu-Pons J." }, { "name": "Centeno E." }, { "name": "Garcia-Garcia J." }, { "name": "Sanz F." }, { "name": "Furlong L.I." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/btq538", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "DisGeNET: A Cytoscape plugin to visualize, integrate, search and analyze gene-disease networks", "abstract": "Summary: DisGeNET is a plugin for Cytoscape to query and analyze human gene-disease networks. DisGeNET allows user-friendly access to a new gene-disease database that we have developed by integrating data from several public sources. DisGeNET permits queries restricted to (i) the original data source, (ii) the association type, (iii) the disease class or (iv) specific gene(s)/disease(s). It represents gene-disease associations in terms of bipartite graphs and provides gene centric and disease centric views of the data. It assists the user in the interpretation and exploration of the genetic basis of human diseases by a variety of built-in functions. Moreover, DisGeNET permits multicolouring of nodes (genes/diseases) according to standard disease classification for expedient visualization. © The Author 2010. Published by Oxford University Press. All rights reserved.", "date": "2010-11-01T00:00:00Z", "citationCount": 177, "authors": [ { "name": "Bauer-Mehren A." }, { "name": "Rautschka M." }, { "name": "Sanz F." }, { "name": "Furlong L.I." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bioinformatics/btw214", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "DisGeNET-RDF: Harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases", "abstract": "Motivation: DisGeNET-RDF makes available knowledge on the genetic basis of human diseases in the Semantic Web. Gene-disease associations (GDAs) and their provenance metadata are published as human-readable and machine-processable web resources. The information on GDAs included in DisGeNET-RDF is interlinked to other biomedical databases to support the development of bioinformatics approaches for translational research through evidence-based exploitation of a rich and fully interconnected linked open data. Availability and implementation: http://rdf.disgenet.org/ Contact:", "date": "2016-07-15T00:00:00Z", "citationCount": 45, "authors": [ { "name": "Queralt-Rosinach N." }, { "name": "Pinero J." }, { "name": "Bravo A." }, { "name": "Sanz F." }, { "name": "Furlong L.I." } ], "journal": "Bioinformatics" } }, { "doi": "10.1371/journal.pone.0020284", "pmid": null, "pmcid": null, "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases", "abstract": "Background: Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult. Principal Findings: We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell. Conclusions: For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases. Availability: The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download. © 2011 Bauer-Mehren et al.", "date": "2011-06-20T00:00:00Z", "citationCount": 140, "authors": [ { "name": "Bauer-Mehren A." }, { "name": "Bundschus M." }, { "name": "Rautschka M." }, { "name": "Mayer M.A." }, { "name": "Sanz F." }, { "name": "Furlong L.I." } ], "journal": "PLoS ONE" } }, { "doi": "10.1093/nar/gkw943", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "DisGeNET: A comprehensive platform integrating information on human disease-associated genes and variants", "abstract": "The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.", "date": "2017-01-01T00:00:00Z", "citationCount": 1604, "authors": [ { "name": "Pinero J." }, { "name": "Bravo A." }, { "name": "Queralt-Rosinach N." }, { "name": "Gutierrez-Sacristan A." }, { "name": "Deu-Pons J." }, { "name": "Centeno E." }, { "name": "Garcia-Garcia J." }, { "name": "Sanz F." }, { "name": "Furlong L.I." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkz1021", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The DisGeNET knowledge platform for disease genomics: 2019 update", "abstract": "One of the most pressing challenges in genomic medicine is to understand the role played by genetic variation in health and disease. Thanks to the exploration of genomic variants at large scale, hundreds of thousands of disease-Associated loci have been uncovered. However, the identification of variants of clinical relevance is a significant challenge that requires comprehensive interrogation of previous knowledge and linkage to new experimental results. To assist in this complex task, we created DisGeNET (http://www.disgenet.org/), a knowledge management platform integrating and standardizing data about disease associated genes and variants from multiple sources, including the scientific literature. DisGeNET covers the full spectrum of human diseases as well as normal and abnormal traits. The current release covers more than 24 000 diseases and traits, 17 000 genes and 117 000 genomic variants. The latest developments of DisGeNET include new sources of data, novel data attributes and prioritization metrics, a redesigned web interface and recently launched APIs. Thanks to the data standardization, the combination of expert curated information with data automatically mined from the scientific literature, and a suite of tools for accessing its publicly available data, DisGeNET is an interoperable resource supporting a variety of applications in genomic medicine and drug R&D.", "date": "2020-01-01T00:00:00Z", "citationCount": 1444, "authors": [ { "name": "Pinero J." }, { "name": "Ramirez-Anguita J.M." }, { "name": "Sauch-Pitarch J." }, { "name": "Ronzano F." }, { "name": "Centeno E." }, { "name": "Sanz F." }, { "name": "Furlong L.I." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Janet Piñero", "email": "janet.pinero@disgenet.com", "url": "https://www.linkedin.com/in/janet-pinero/", "orcidid": "http://orcid.org/0000-0003-1244-7654", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Developer", "Maintainer", "Support" ], "note": null }, { "name": "Laura I. Furlong", "email": "laura.furlong@disgenet.com", "url": "https://www.linkedin.com/in/laura-ines-furlong-668b9a5/", "orcidid": "https://orcid.org/0000-0002-9383-528X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Contributor", "Documentor", "Support" ], "note": null }, { "name": "Ferran Sanz", "email": "ferran.sanz@upf.edu", "url": null, "orcidid": "http://orcid.org/0000-0002-7534-7661", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "community": null, "owner": "lfurlong", "additionDate": "2016-04-06T15:00:43Z", "lastUpdate": "2024-07-10T12:56:33.065303Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-EE", "lfurlong", "janet.pinero" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MSFragger", "description": "A database search tool for performing mass spectometry data similarity comparisons. For that it uses a fragment ion indexing method.", "homepage": "http://www.nesvilab.org/software", "biotoolsID": "msfragger", "biotoolsCURIE": "biotools:msfragger", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3646", "term": "Peptide database search" }, { "uri": "http://edamontology.org/operation_3801", "term": "Spectral library search" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" }, { "uri": "http://edamontology.org/format_3651", "term": "MGF" }, { "uri": "http://edamontology.org/format_3712", "term": "Thermo RAW" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0945", "term": "Peptide identification" }, "format": [ { "uri": "http://edamontology.org/format_3655", "term": "pepXML" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_0601", "term": "Protein modifications" } ], "operatingSystem": [], "language": [ "Java" ], "license": "Other", "collectionID": [ "Proteomics" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "http://www.nesvilab.org/software", "type": "Source code", "note": null, "version": null } ], "documentation": [], "publication": [ { "doi": "10.1038/nmeth.4256", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "MSFragger: Ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics", "abstract": "There is a need to better understand and handle the 'dark matter' of proteomics-the vast diversity of post-translational and chemical modifications that are unaccounted in a typical mass spectrometry-based analysis and thus remain unidentified. We present a fragment-ion indexing method, and its implementation in peptide identification tool MSFragger, that enables a more than 100-fold improvement in speed over most existing proteome database search tools. Using several large proteomic data sets, we demonstrate how MSFragger empowers the open database search concept for comprehensive identification of peptides and all their modified forms, uncovering dramatic differences in modification rates across experimental samples and conditions. We further illustrate its utility using protein-RNA cross-linked peptide data and using affinity purification experiments where we observe, on average, a 300% increase in the number of identified spectra for enriched proteins. We also discuss the benefits of open searching for improved false discovery rate estimation in proteomics.", "date": "2017-04-27T00:00:00Z", "citationCount": 877, "authors": [ { "name": "Kong A.T." }, { "name": "Leprevost F.V." }, { "name": "Avtonomov D.M." }, { "name": "Mellacheruvu D." }, { "name": "Nesvizhskii A.I." } ], "journal": "Nature Methods" } } ], "credit": [ { "name": "Alexey Nesvizhskii", "email": "nesvi@umich.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "ELIXIR-EE", "additionDate": "2018-06-11T09:48:30Z", "lastUpdate": "2024-07-10T10:06:37.289299Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "n.m.palmblad@lumc.nl" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "trimAl", "description": "Tool for the automated removal of spurious sequences or poorly aligned regions from a multiple sequence alignment.", "homepage": "https://trimal.readthedocs.io", "biotoolsID": "trimal", "biotoolsCURIE": "biotools:trimal", "version": [ "1.5.0", "2.0-RC" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0492", "term": "Multiple sequence alignment" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0863", "term": "Sequence alignment" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1916", "term": "Alignment" }, "format": [ { "uri": "http://edamontology.org/format_1982", "term": "ClustalW format" }, { "uri": "http://edamontology.org/format_1997", "term": "PHYLIP format" }, { "uri": "http://edamontology.org/format_1998", "term": "phylipnon" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" }, { "uri": "http://edamontology.org/topic_0160", "term": "Sequence sites, features and motifs" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++" ], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/inab/trimal", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/inab/trimal", "type": "Source code", "note": null, "version": "1.5.0" }, { "url": "https://github.com/inab/trimal/tree/2.0_RC", "type": "Source code", "note": null, "version": "2.0-RC" } ], "documentation": [ { "url": "http://trimal.cgenomics.org/", "type": [ "General" ], "note": "Old versions" }, { "url": "https://trimal.readthedocs.io", "type": [ "General" ], "note": null } ], "publication": [ { "doi": null, "pmid": "19505945", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "trimAl: A tool for automated alignment trimming in large-scale phylogenetic analyses", "abstract": "Multiple sequence alignments are central to many areas of bioinformatics. It has been shown that the removal of poorly aligned regions from an alignment increases the quality of subsequent analyses. Such an alignment trimming phase is complicated in large-scale phylogenetic analyses that deal with thousands of alignments. Here, we present trimAl, a tool for automated alignment trimming, which is especially suited for large-scale phylogenetic analyses. trimAl can consider several parameters, alone or in multiple combinations, for selecting the most reliable positions in the alignment. These include the proportion of sequences with a gap, the level of amino acid similarity and, if several alignments for the same set of sequences are provided, the level of consistency across different alignments. Moreover, trimAl can automatically select the parameters to be used in each specific alignment so that the signal-to-noise ratio is optimized. © 2009 The Author(s).", "date": "2009-08-01T00:00:00Z", "citationCount": 6392, "authors": [ { "name": "Capella-Gutierrez S." }, { "name": "Silla-Martinez J.M." }, { "name": "Gabaldon T." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Salvador Capella-Gutierrez", "email": "salcagu@gmail.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": null, "email": "tgabaldon@crg.es", "url": "http://gabaldonlab.crg.es/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "scapella", "additionDate": "2017-04-15T08:42:53Z", "lastUpdate": "2024-07-02T16:07:19.710886Z", "editPermission": { "type": "group", "authors": [ "nico_bsc", "sergitobara" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Smoother", "description": "Smoother is an interactive analysis and visualization software for nucleic acid interactome data (e.g. Hi-C data) that allows the change of parameters such as normalization, bin size, or MAPQ, on-the-fly. Smoother can load multiple samples which can be grouped and compared. Smoother also allows filtering by annotations and the display of coverage for additional sequencing data.\n\nSmoother is centered around an index including the genome, annotations, and datasets to be analyzed and visualized. Using this index, Smoother allows changing analysis parameters on-the-fly.\n\nInstall: pip install biosmoother", "homepage": "https://biosmoother.readthedocs.io/en/latest/", "biotoolsID": "smoother", "biotoolsCURIE": "biotools:smoother", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3940", "term": "Chromosome conformation capture" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python", "C++" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Siegel-Lab/BioSmoother", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://biosmoother.readthedocs.io/en/latest/", "type": [ "User manual", "API documentation", "Citation instructions", "Installation instructions" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkae008", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Smoother: on-the-fly processing of int er act ome data using prefix sums", "abstract": "Nucleic acid interactome data, such as chromosome conformation capture data and RNA-DNA interactome data, are currently analyzed via pipelines that must be rerun for each new parameter set. A more dynamic approach is desirable since the optimal parameter set is commonly unknown ahead of time and rerunning pipelines is a time-consuming process. We ha v e de v eloped an approach fast enough to process interac- tome data on-the-fly using a sparse prefix sum index. With this inde x, w e created Smoother, a flexible, multifeatured visualization and analysis tool that allo ws interactiv e filtering , e.g . by mapping qualit y, almost inst ant comparisons bet ween different normalization approaches, e.g . iterative cor rection, and ploidy cor rection. Further, Smoother can o v erla y other sequencing data or genomic annotations, compare different samples, and perform virtual 4C analysis. Smoother permits a novel way to interact with and explore interactome data, fostering comprehensive, high-quality data analysis. Smoother is available at https: // github.com / Siegel-Lab / BioSmoother under the MIT license.", "date": "2024-03-21T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Schmidt M.R." }, { "name": "Barcons-Simon A." }, { "name": "Rabuffo C." }, { "name": "Siegel T.N." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Markus Schmidt", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-5601-6349", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "community": null, "owner": "MarkusSchmidt", "additionDate": "2024-06-26T13:54:39.637629Z", "lastUpdate": "2024-06-26T14:01:54.743661Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "iVar", "description": "iVar is a computational package that contains functions broadly useful for viral amplicon-based sequencing.", "homepage": "https://andersen-lab.github.io/ivar/html/", "biotoolsID": "andersen-lab_ivar", "biotoolsCURIE": "biotools:andersen-lab_ivar", "version": [ "1.4.3" ], "otherID": [], "relation": [ { "biotoolsID": "samtools", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3237", "term": "Primer removal" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Suite" ], "topic": [ { "uri": "http://edamontology.org/topic_0781", "term": "Virology" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "C++" ], "license": "GPL-3.0", "collectionID": [ "COVID-19" ], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [ "Tools" ], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/andersen-lab/ivar", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/s13059-018-1618-7", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar", "abstract": "How viruses evolve within hosts can dictate infection outcomes; however, reconstructing this process is challenging. We evaluate our multiplexed amplicon approach, PrimalSeq, to demonstrate how virus concentration, sequencing coverage, primer mismatches, and replicates influence the accuracy of measuring intrahost virus diversity. We develop an experimental protocol and computational tool, iVar, for using PrimalSeq to measure virus diversity using Illumina and compare the results to Oxford Nanopore sequencing. We demonstrate the utility of PrimalSeq by measuring Zika and West Nile virus diversity from varied sample types and show that the accumulation of genetic diversity is influenced by experimental and biological systems.", "date": "2019-01-08T00:00:00Z", "citationCount": 499, "authors": [ { "name": "Grubaugh N.D." }, { "name": "Gangavarapu K." }, { "name": "Quick J." }, { "name": "Matteson N.L." }, { "name": "De Jesus J.G." }, { "name": "Main B.J." }, { "name": "Tan A.L." }, { "name": "Paul L.M." }, { "name": "Brackney D.E." }, { "name": "Grewal S." }, { "name": "Gurfield N." }, { "name": "Van Rompay K.K.A." }, { "name": "Isern S." }, { "name": "Michael S.F." }, { "name": "Coffey L.L." }, { "name": "Loman N.J." }, { "name": "Andersen K.G." } ], "journal": "Genome Biology" } } ], "credit": [], "community": null, "owner": "wm75", "additionDate": "2024-06-21T11:15:18.246716Z", "lastUpdate": "2024-06-21T11:15:18.252160Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ClinData", "description": "Comprehensive information system for data stewardship in clinical trials, registries and other clinical/scientific databases. 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In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol∗ development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol∗ Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. 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