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Strictly evidence-based, no ML determines pathogenicity." }, { "url": "https://folklore.helena.bio/methodology/mtdna", "type": [ "General" ], "note": "Mitochondrial DNA variant classification under the ClinGen Mitochondrial Disease Working Group (MMDWG) 2020 specification (McCormick et al. 2020). Operates as an independent module from the nuclear ACMG/AMP pipeline; every variant carries an explicit framework provenance label. Strength tiers follow ClinGen mtDNA VCEP v1.0.0." }, { "url": "https://folklore.helena.bio/methodology/family-analysis", "type": [ "General" ], "note": "Inheritance-aware evidence from trio (proband + both parents), duo, and proband-plus-sibling analyses. Implements ClinGen SVI 2018 de novo PS2/PM6 (PMID 29543229), Jarvik & Browning 2016 LOD segregation framework (PMID 27236918), and ClinGen SVI 2021 PP1 strength bands. 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Computes the Bhattacharyya Coefficient (BC) and the Root Mean Squared Inner Product (RMSIP) of aligned parts of the proteins. Alignment of sets of proteins to be compared. Multiple protein structures Heatmaps, dendrograms and structural amino acid profiles for visual comparison of structural similarity. White space delimited tabular data for the provided plots", "cmd": null } ], "toolType": [ "Web API", "Suite" ], "topic": [ { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0736", "term": "Protein folds and structural domains" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [ "BiB tools", "CBU tools", "UiB tools", "ELIXIR-NO", "ELIXIR-Norway" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Norway" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [ { "url": "https://github.com/reuter-group/webnma3", "type": [ "Repository", "Issue tracker" ], "note": null }, { "url": "https://elixir.no/helpdesk", "type": [ "Helpdesk" ], "note": "Helpdesk and support for ELIXIR Norway services." } ], "download": [], "documentation": [ { "url": "http://apps.cbu.uib.no/webnma3/howto/single", "type": [ "Quick start guide" ], "note": null }, { "url": "http://apps.cbu.uib.no/webnma3/qanda", "type": [ "FAQ" ], "note": null }, { "url": "http://apps.cbu.uib.no/webnma3/about", "type": [ "General", "Citation instructions" ], "note": null } ], "publication": [ { "doi": "10.1186/s12859-014-0427-6", "pmid": "25547242", "pmcid": "PMC4339738", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "WEBnmat v2.0: Web server and services for comparing protein flexibility", "abstract": "Background: Normal mode analysis (NMA) using elastic network models is a reliable and cost-effective computational method to characterise protein flexibility and by extension, their dynamics. Further insight into the dynamics-function relationship can be gained by comparing protein motions between protein homologs and functional classifications. This can be achieved by comparing normal modes obtained from sets of evolutionary related proteins. Results: We have developed an automated tool for comparative NMA of a set of pre-aligned protein structures. The user can submit a sequence alignment in the FASTA format and the corresponding coordinate files in the Protein Data Bank (PDB) format. The computed normalised squared atomic fluctuations and atomic deformation energies of the submitted structures can be easily compared on graphs provided by the web user interface. The web server provides pairwise comparison of the dynamics of all proteins included in the submitted set using two measures: the Root Mean Squared Inner Product and the Bhattacharyya Coefficient. The Comparative Analysis has been implemented on our web server for NMA, WEBnmat, which also provides recently upgraded functionality for NMA of single protein structures. This includes new visualisations of protein motion, visualisation of inter-residue correlations and the analysis of conformational change using the. In addition, programmatic access to WEBnmat is now available through a SOAP-based web service. WEBnmat is available at. Conclusion: WEBnmat v2.0 is an online tool offering unique capability for comparative NMA on multiple protein structures. Along with a convenient web interface, powerful computing resources, and several methods for mode analyses, WEBnmat facilitates the assessment of protein flexibility within protein families and superfamilies. These analyses can give a good view of how the structures move and how the flexibility is conserved over the different structures.", "date": "2014-12-30T00:00:00Z", "citationCount": 87, "authors": [ { "name": "Tiwari S.P." }, { "name": "Fuglebakk E." }, { "name": "Hollup S.M." }, { "name": "Skjaerven L." }, { "name": "Cragnolini T." }, { "name": "Grindhaug S.H." }, { "name": "Tekle K.M." }, { "name": "Reuter N." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1186/1471-2105-6-52", "pmid": "15762993", "pmcid": "PMC1274249", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "WEBnm@: A web application for normal mode analyses of proteins", "abstract": "Background: Normal mode analysis (NMA) has become the method of choice to investigate the slowest motions in macromolecular systems. NMA is especially useful for large biomolecular assemblies, such as transmembrane channels or virus capsids. NMA relies on the hypothesis that the vibrational normal modes having the lowest frequencies (also named soft modes) describe the largest movements in a protein and are the ones that are functionally relevant. Results: We developed a web-based server to perform normal modes calculations and different types of analyses. Starting from a structure file provided by the user in the PDB format, the server calculates the normal modes and subsequently offers the user a series of automated calculations; normalized squared atomic displacements, vector field representation and animation of the first six vibrational modes. Each analysis is performed independently from the others and results can be visualized using only a web browser. No additional plug-in or software is required. For users who would like to analyze the results with their favorite software, raw results can also be downloaded. The application is available on http://www.bioinfo.no/tools/normalmodes. We present here the underlying theory, the application architecture and an illustration of its features using a large transmembrane protein as an example. Conclusion: We built an efficient and modular web application for normal mode analysis of proteins. 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"http://edamontology.org/topic_3386", "term": "Laboratory animal science" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [], "language": [ "JavaScript" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://gcanudo-barreras.github.io/ViVo-Platform/", "type": [ "Service" ], "note": null }, { "url": "https://www.biorxiv.org/content/10.1101/2025.10.14.682266v1", "type": [ "Other" ], "note": "bioRxiv preprint" }, { "url": "https://github.com/gcanudo-barreras/ViVo-Platform", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/gcanudo-barreras/ViVo-Platform/blob/main/README.md", "type": [ "General" ], "note": null }, { "url": "https://github.com/gcanudo-barreras/ViVo-Platform/blob/main/ViVo_USER_MANUAL.md", "type": [ "User manual" ], "note": null }, { "url": "https://www.biorxiv.org/content/10.1101/2025.10.14.682266v1", "type": [ "Other" ], "note": "Full methodology" }, { "url": "https://github.com/gcanudo-barreras/ViVo-Platform/releases/tag/v1.0-beta", "type": [ "Release notes" ], "note": null } ], "publication": [ { "doi": "10.1101/2025.10.14.682266", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": "Research Beta 1.0", "note": null, "metadata": null } ], "credit": [ { "name": "Guillermo Canudo-Barreras", "email": "canudobarreras@unizar.es", "url": null, "orcidid": "https://orcid.org/0000-0002-1949-9185", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact", "Maintainer", "Support" ], "note": "Researcher at Spanish National Research Council (CSIC). Developer." }, { "name": "Eduardo Romanos", "email": "eromanos.iacs@aragon.es", "url": null, "orcidid": "https://orcid.org/0000-0002-9918-3374", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Researcher at Biomedical Research Center of Aragon (CIBA)." }, { "name": "Raquel P. Herrera", "email": "raquelph@unizar.es", "url": null, "orcidid": "https://orcid.org/0000-0002-5244-9569", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Senior scientist at Spanish National Research Council (CSIC)." }, { "name": "M. Concepción Gimeno", "email": "gimeno@unizar.es", "url": null, "orcidid": "https://orcid.org/0000-0003-0553-0695", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Full professor at Spanish National Research Council (CSIC)." } ], "owner": "gcanudo-barreras", "additionDate": "2025-10-23T09:01:44.958137Z", "lastUpdate": "2025-10-23T09:09:29.560348Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MaCPepDB - Mass Centric Peptide Database", "description": "A Database to Quickly Access All Tryptic Peptides of the UniProtKB", "homepage": "https://macpepdb.cubimed.rub.de/", "biotoolsID": "macpepdb_-_mass_centric_peptide_database", "biotoolsCURIE": "biotools:macpepdb_-_mass_centric_peptide_database", "version": [ "3.0.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [], "language": [ "Rust", "JavaScript", "Other" ], "license": null, "collectionID": [ "CUBiMed.RUB", "BioInfra.Prot" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/medbioinf/macpepdb", "type": [ "Repository" ], "note": "Backend implementation written in Rust / Axum" }, { "url": "https://github.com/medbioinf/macpepdb-frontend", "type": [ "Repository" ], "note": "Frontend implementation written in Rust / Dioxus" } ], "download": [], "documentation": [ { "url": "https://docs.rs/macpepdb/latest/macpepdb/web/index.html", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jproteome.0c00967", "pmid": "33724838", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "MaCPepDB: A Database to Quickly Access All Tryptic Peptides of the UniProtKB", "abstract": "Protein sequence databases play a crucial role in the majority of the currently applied mass-spectrometry-based proteomics workflows. Here UniProtKB serves as one of the major sources, as it combines the information of several smaller databases and enriches the entries with additional biological information. For the identification of peptides in a sample by tandem mass spectra, as generated by data-dependent acquisition, protein sequence databases provide the basis for most spectrum identification search engines. In addition, for targeted proteomics approaches like selected reaction monitoring (SRM) and parallel reaction monitoring (PRM), knowledge of the peptide sequences, their masses, and whether they are unique for a protein is essential. Because most bottom-up proteomics approaches use trypsin to cleave the proteins in a sample, the tryptic peptides contained in a protein database are of great interest. We present a database, called MaCPepDB (mass-centric peptide database), that consists of the complete tryptic digest of the Swiss-Prot and TrEMBL parts of UniProtKB. This database is especially designed to not only allow queries of peptide sequences and return the respective information about connected proteins and thus whether a peptide is unique but also allow queries of specific masses of peptides or precursors of MS/MS spectra. Furthermore, posttranslational modifications can be considered in a query as well as different mass deviations for posttranslational modifications. Hence the database can be used by a sequence query not only to, for example, check in which proteins of the UniProt database a tryptic peptide can be found but also to find possibly interfering peptides in PRM/SRM experiments using the mass query. The complete database contains currently 5 939 244 990 peptides from 185 561 610 proteins (UniProt version 2020_03), for which a single query usually takes less than 1 s. For easy exploration of the data, a web interface was developed. A REST application programming interface (API) for programmatic and workflow access is also available at https://macpepdb.mpc.rub.de.", "date": "2021-04-02T00:00:00Z", "citationCount": 9, "authors": [ { "name": "Uszkoreit J." }, { "name": "Winkelhardt D." }, { "name": "Barkovits K." }, { "name": "Wulf M." }, { "name": "Roocke S." }, { "name": "Marcus K." }, { "name": "Eisenacher M." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Julian Uszkoreit", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0001-7522-4007", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Dirk Winkelhardt", "email": "dirk.winkelhardt@rub.de", "url": null, "orcidid": "https://orcid.org/0000-0001-8770-2221", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "PD Dr. Martin Eisenacher", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-2687-7444", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "di_hardt", "additionDate": "2023-07-25T12:35:27.605861Z", "lastUpdate": "2025-07-31T09:03:29.192901Z", "editPermission": { "type": "group", "authors": [ "di_hardt", "julianu", "BioInfra.Prot" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MirGeneDB", "description": "MirGeneDB is a database of manually curated microRNA genes that have been validated and annotated as initially described in Fromm et al. 2015 , Fromm et al. 2020 and Fromm et al 2022. MirGeneDB 3.0 (Clarke and Hoye et al. 2024 ) includes more than 21,000 microRNA gene entries representing more than 1,700 microRNA families from 114 metazoan species. All microRNAs can be browsed, searched and downloaded.", "homepage": "http://mirgenedb.org/", "biotoolsID": "mirgen", "biotoolsCURIE": "biotools:mirgen", "version": [ "3.0" ], "otherID": [ { "value": "doi:10.25504/FAIRsharing.QXSgvF", "type": "doi", "version": "2.0" } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_0564", "term": "Sequence visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_1869", "term": "Organism identifier" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3134", "term": "Gene transcript report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] }, { "data": { "uri": "http://edamontology.org/data_0880", "term": "RNA secondary structure" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "Data retrieval: curated miRNA. Organism identifier: a specific miRNA identifier or a species for all miRNAs for that species. Gene transcript report: with metadata and visualization. RNA secondary structure: the hairpin loop of the miRNA with bases.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3495", "term": "RNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_2012", "term": "Sequence coordinates" }, "format": [ { "uri": "http://edamontology.org/format_2305", "term": "GFF" }, { "uri": "http://edamontology.org/format_3003", "term": "BED" } ] }, { "data": { "uri": "http://edamontology.org/data_3917", "term": "Count matrix" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" }, { "uri": "http://edamontology.org/topic_3299", "term": "Evolutionary biology" }, { "uri": "http://edamontology.org/topic_3500", "term": "Zoology" }, { "uri": "http://edamontology.org/topic_2815", "term": "Human biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "CC0-1.0", "collectionID": [ "UiO tools", "ELIXIR-NO", "ELIXIR-Norway" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Norway" ], "elixirCommunity": [], "link": [ { "url": "https://elixir.no/helpdesk", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://www.mirgenedb.org/download", "type": "Biological data", "note": "Sequence downloads for 75 species", "version": "3.0" } ], "documentation": [ { "url": "https://www.mirgenedb.org/information", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkab1101", "pmid": "34850127", "pmcid": "PMC8728216", "type": [ "Primary" ], "version": "2.1", "note": null, "metadata": { "title": "MirGeneDB 2.1: Toward a complete sampling of all major animal phyla", "abstract": "We describe an update of MirGeneDB, the manually curated microRNA gene database. Adhering to uniform and consistent criteria for microRNA annotation and nomenclature, we substantially expanded MirGeneDB with 30 additional species representing previously missing metazoan phyla such as sponges, jellyfish, rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning over ∼800 million years of animal evolution, and contains a total number of 16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new phylogenetically important species, especially those relevant for the study of whole genome duplication events, and through updating evolutionary nodes of origin for many families and genes, we were able to substantially refine our nomenclature system. All changes are traceable in the specifically developed MirGeneDB version tracker. The performance of read-pages is improved and microRNA expression matrices for all tissues and species are now also downloadable. Altogether, this update represents a significant step toward a complete sampling of all major metazoan phyla, and a widely needed foundation for comparative microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.", "date": "2022-01-07T00:00:00Z", "citationCount": 95, "authors": [ { "name": "Fromm B." }, { "name": "Hoye E." }, { "name": "Domanska D." }, { "name": "Zhong X." }, { "name": "Aparicio-Puerta E." }, { "name": "Ovchinnikov V." }, { "name": "Umu S.U." }, { "name": "Chabot P.J." }, { "name": "Kang W." }, { "name": "Aslanzadeh M." }, { "name": "Tarbier M." }, { "name": "Marmol-Sanchez E." }, { "name": "Urgese G." }, { "name": "Johansen M." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Friedlander M.R." }, { "name": "Peterson K.J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkz885", "pmid": "31598695", "pmcid": "PMC6943042", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "MirGeneDB 2.0: The metazoan microRNA complement", "abstract": "Small non-coding RNAs have gained substantial attention due to their roles in animal development and human disorders. Among them, microRNAs are special because individual gene sequences are conserved across the animal kingdom. In addition, unique and mechanistically well understood features can clearly distinguish bona fide miRNAs from the myriad other small RNAs generated by cells. However, making this distinction is not a common practice and, thus, not surprisingly, the heterogeneous quality of available miRNA complements has become a major concern in microRNA research. We addressed this by extensively expanding our curated microRNA gene database-MirGeneDB-to 45 organisms, encompassing a wide phylogenetic swath of animal evolution. By consistently annotating and naming 10,899 microRNA genes in these organisms, we show that previous microRNA annotations contained not only many false positives, but surprisingly lacked >2000 bona fide microRNAs. Indeed, curated microRNA complements of closely related organisms are very similar and can be used to reconstruct ancestral miRNA repertoires. MirGeneDB represents a robust platform for microRNA-based research, providing deeper and more significant insights into the biology and evolution of miRNAs as well as biomedical and biomarker research. MirGeneDB is publicly and freely available at http://mirgenedb.org/.", "date": "2020-01-01T00:00:00Z", "citationCount": 178, "authors": [ { "name": "Fromm B." }, { "name": "Domanska D." }, { "name": "Hoye E." }, { "name": "Ovchinnikov V." }, { "name": "Kang W." }, { "name": "Aparicio-Puerta E." }, { "name": "Johansen M." }, { "name": "Flatmark K." }, { "name": "Mathelier A." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Friedlander M.R." }, { "name": "Peterson K.J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1146/annurev-genet-120213-092023", "pmid": "26473382", "pmcid": "PMC4743252", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "A Uniform System for the Annotation of Vertebrate microRNA Genes and the Evolution of the Human microRNAome", "abstract": "Although microRNAs (miRNAs) are among the most intensively studied molecules of the past 20 years, determining what is and what is not a miRNA has not been straightforward. Here, we present a uniform system for the annotation and nomenclature of miRNA genes. We show that less than a third of the 1,881 human miRBase entries, and only approximately 16% of the 7,095 metazoan miRBase entries, are robustly supported as miRNA genes. Furthermore, we show that the human repertoire of miRNAs has been shaped by periods of intense miRNA innovation and that mature gene products show a very different tempo and mode of sequence evolution than star products. We establish a new open access database-MirGeneDB (http://mirgenedb.org)-to catalog this set of miRNAs, which complements the efforts of miRBase but differs from it by annotating the mature versus star products and by imposing an evolutionary hierarchy upon this curated and consistently named repertoire.", "date": "2015-11-23T00:00:00Z", "citationCount": 435, "authors": [ { "name": "Fromm B." }, { "name": "Billipp T." }, { "name": "Peck L.E." }, { "name": "Johansen M." }, { "name": "Tarver J.E." }, { "name": "King B.L." }, { "name": "Newcomb J.M." }, { "name": "Sempere L.F." }, { "name": "Flatmark K." }, { "name": "Hovig E." }, { "name": "Peterson K.J." } ], "journal": "Annual Review of Genetics" } }, { "doi": "10.1093/nar/gkae1094", "pmid": "39673268", "pmcid": "PMC11701709", "type": [ "Primary" ], "version": "3.0", "note": null, "metadata": { "title": "MirGeneDB 3.0: Improved taxonomic sampling, uniform nomenclature of novel conserved microRNA families and updated covariance models", "abstract": "We present a major update of MirGeneDB (3.0), the manually curated animal microRNA gene database. Beyond moving to a new server and the creation of a computational mirror, we have expanded the database with the addition of 33 invertebrate species, including representatives of 5 previously unsampled phyla, and 6 mammal species. MirGeneDB now contains entries for 21 822 microRNA genes (5160 of these from the new species) belonging to 1743 microRNA families. The inclusion of these new species allowed us to refine both the evolutionary node of appearance of a number of microRNA genes/families, as well as MirGeneDB's phylogenetically informed nomenclature system. Updated covariance models of all microRNA families, along with all smallRNA read data are now downloadable. These enhanced annotations will allow researchers to analyze microRNA properties such as secondary structure and features of their biogenesis within a robust phylogenetic context and without the database plagued with numerous false positives and false negatives. In light of these improvements, MirGeneDB 3.0 will assume the responsibility for naming conserved novel metazoan microRNAs. MirGeneDB is part of RNAcentral and Elixir Norway and is publicly and freely available at mirgenedb.org.", "date": "2025-01-06T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Clarke A.W." }, { "name": "Hoye E." }, { "name": "Hembrom A.A." }, { "name": "Paynter V.M." }, { "name": "Vinther J." }, { "name": "Wyrozemski L." }, { "name": "Biryukova I." }, { "name": "Formaggioni A." }, { "name": "Ovchinnikov V." }, { "name": "Herlyn H." }, { "name": "Pierce A." }, { "name": "Wu C." }, { "name": "Aslanzadeh M." }, { "name": "Cheneby J." }, { "name": "Martinez P." }, { "name": "Friedlander M.R." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Umu S.U." }, { "name": "Johansen M." }, { "name": "Peterson K.J." }, { "name": "Fromm B." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Bastian Fromm", "email": "BastianFromm@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-0352-3037", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer", "Support" ], "note": null }, { "name": "Kevin J. 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Results Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. Availability and implementation DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. 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"uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_2878", "term": "Protein structural motif" }, "format": [ { "uri": "http://edamontology.org/format_2332", "term": "XML" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_1317", "term": "Structural biology" }, { "uri": "http://edamontology.org/topic_3306", "term": "Biophysics" }, { "uri": "http://edamontology.org/topic_0123", "term": "Protein properties" }, { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_0821", "term": "Enzymes" }, { "uri": "http://edamontology.org/topic_0820", "term": "Membrane and lipoproteins" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_3068", "term": "Literature and language" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript", "C#" ], "license": "Freeware", "collectionID": [ "LCC NCBR", "ELIXIR-CZ" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [ { "url": "https://channelsdb2.biodata.ceitec.cz", "type": [ "Service" ], "note": null } ], "download": [], "documentation": [ { "url": "https://channelsdb2.biodata.ceitec.cz/documentation.html", "type": [ "User manual", "Quick start guide" ], "note": "Database content\nChannels nomenclature\nMOLE settings\nList of cofactors used for channel determination.\nDescription how to read the resuls page.\nHow to access content of the database programatically." }, { "url": "https://channelsdb2.biodata.ceitec.cz/methods.html", "type": [ "General", "FAQ" ], "note": "Info about methodology" }, { "url": "https://channelsdb2.biodata.ceitec.cz/about.html", "type": [ "Citation instructions", "Contributions policy" ], "note": null }, { "url": "https://channelsdb2.biodata.ceitec.cz/api", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkx868", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": "1.0", "note": null, "metadata": { "title": "ChannelsDB: Database of biomacromolecular tunnels and pores", "abstract": "ChannelsDB (http://ncbr.muni.cz/ChannelsDB) is a database providing information about the positions, geometry and physicochemical properties of channels (pores and tunnels) found within biomacromolecular structures deposited in the Protein Data Bank. Channels were deposited from two sources; from literature using manual deposition and from a software tool automatically detecting tunnels leading to the enzymatic active sites and selected cofactors, and transmembrane pores. The database stores information about geometrical features (e.g. length and radius profile along a channel) and physicochemical properties involving polarity, hydrophobicity, hydropathy, charge and mutability. The stored data are interlinked with available UniProt annotation data mapping known mutation effects to channel-lining residues. All structures with channels are displayed in a clear interactive manner, further facilitating data manipulation and interpretation. As such, ChannelsDB provides an invaluable resource for research related to deciphering the biological function of biomacromolecular channels.", "date": "2018-01-01T00:00:00Z", "citationCount": 29, "authors": [ { "name": "Pravda L." }, { "name": "Sehnal D." }, { "name": "Svobodova VaEkova R." }, { "name": "Navratilova V." }, { "name": "Tousek D." }, { "name": "Berka K." }, { "name": "Otyepka M." }, { "name": "Koca J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkad1012", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "ChannelsDB 2.0:ã comprehensive database of protein tunnelsãnd pores in Alpha Foldera", "abstract": "ChannelsDB 2.0 isãn updated database providing str uct ural informationãbout the position, geometryãnd ph y sicochemical properties of protein channels-tunnelsãnd pores-within deposited biomacromolecular str uct ures from PDBãnd AlphaFoldDB databases. T he ne wly deposited information originated from several sources. Firstly, we included data calculated usingã popular CAVER tool to complement the datã obtãined using original MOLE tool for detectionãndãnalysis of protein tunnelsãnd pores. Secondly, weãdded tunnels starting from cofactors within the AlphaFill database to enlarge the scope of the database to protein models based on Uniprot. This has enlargedã vãilable channelãnnotations ∼4.6 timesãs of 1 September 2023. The database stores informationãbout geometrical features, e.g. lengthãnd radius,ãnd ph y sico-chemical properties based on channel-liningãminoãcids. The stored dataãre interlinked with theã vãilable UniP rot mutãtionãnnotãtion datã. ChannelsDB 2.0 providesãn excellent resource for deepãnalysis of the role of biomacromolecular tunnelsãnd pores. The database isãvailable free of charge: ht tps://c hannelsdb2.biodata.ceitec.cz .", "date": "2024-01-05T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Spackova A." }, { "name": "Vavra O." }, { "name": "Racek T." }, { "name": "Bazgier V." }, { "name": "Sehnal D." }, { "name": "Damborsky J." }, { "name": "Svobodova R." }, { "name": "Bednar D." }, { "name": "Berka K." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Lukáš Pravda", "email": "xpravda@ncbr.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-6435-4719", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "David Sehnal", "email": "david.sehnal@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-0682-3089", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Karel Berka", "email": "karel.berka@upol.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-9472-2589", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Contributor" ], "note": null }, { "name": "Radka Svobodová", "email": "radka.svobodova@ceitec.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-3840-8760", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Provider" ], "note": null }, { "name": "David Bednář", "email": "222755@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-6803-0340", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Palacky University Olomouc", "email": null, "url": "https://www.upol.cz/en/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null }, { "name": "Masaryk University Brno", "email": null, "url": "https://www.muni.cz/en", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null }, { "name": "Václav Bazgier", "email": "vaclav.bazgier@upol.cz", "url": null, "orcidid": "https://orcid.org/0000-0003-3393-3010", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Documentor", "Contributor" ], "note": null }, { "name": "Anna Špačková", "email": "anna.spackova@upol.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-7142-3092", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Documentor" ], "note": null }, { "name": "Ondřej Vávra", "email": "vavra@enantis.com", "url": null, "orcidid": "https://orcid.org/0000-0003-1396-2543", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Tomáš Raček", "email": "324965@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-0296-2452", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer" ], "note": null }, { "name": "Jiří Damborský", "email": "jiri@chemi.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-7848-8216", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "ELIXIR-CZ", "additionDate": "2017-08-03T12:46:16Z", "lastUpdate": "2024-11-25T13:45:26.806319Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PROTEOFORMER", "description": "Proteogenomic pipeline integrating ribosome profiling (RIBO-seq) data in the search for new proteoforms in proteomic validation data. The pipeline does a genome-wide construction of candidate translation products based on ribosome occupancy.", "homepage": "https://github.com/Biobix/proteoformer", "biotoolsID": "proteoformer", "biotoolsCURIE": "biotools:proteoformer", "version": [ "1.0", "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2423", "term": "Prediction and recognition" }, { "uri": "http://edamontology.org/operation_3563", "term": "RNA-seq read count analysis" }, { "uri": "http://edamontology.org/operation_3225", "term": "Variant classification" }, { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" }, { "uri": "http://edamontology.org/operation_2284", "term": "Nucleic acid density plotting" }, { "uri": "http://edamontology.org/operation_3198", "term": "Read mapping" }, { "uri": "http://edamontology.org/operation_3182", "term": "Genome alignment" }, { "uri": "http://edamontology.org/operation_3800", "term": "RNA-Seq quantification" }, { "uri": "http://edamontology.org/operation_3661", "term": "SNP annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3496", "term": "RNA sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_3621", "term": "SQLite format" } ] }, { "data": { "uri": "http://edamontology.org/data_2886", "term": "Protein sequence record" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": null, "cmd": "perl mapping.pl --help" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3120", "term": "Protein variants" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "R", "Perl", "SQL", "Python" ], "license": "GPL-3.0", "collectionID": [ "BIG N2N", "Proteomics", "BioBix", "UGent" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Biobix/proteoformer", "type": [ "Repository" ], "note": "GitHub tool repo (PROTEOFORMER version 2.0)" }, { "url": "http://galaxy.ugent.be/", "type": [ "Galaxy service" ], "note": "Galaxy service of PROTEOFORMER version 1.0 (the Galaxy service of PROTEOFORMER version 2.0 is under way)" }, { "url": "http://www.biobix.be/research/downloads/proteoformer/", "type": [ "Other" ], "note": "Explanation of the tool on the lab's website" } ], "download": [ { "url": "https://github.com/Biobix/proteoformer", "type": "Source code", "note": "GitHub repo", "version": "2.0" }, { "url": "https://github.com/Biobix/proteoformer/tree/master/Galaxy%20files", "type": "Tool wrapper (Galaxy)", "note": "Galaxy wrapper files", "version": "1.0" } ], "documentation": [ { "url": "https://github.com/Biobix/proteoformer/blob/master/README.md", "type": [ "User manual" ], "note": "Full elaborate documentation on usage and installation with lots of examples. Main documentation source." }, { "url": "https://github.com/Biobix/proteoformer/blob/master/LICENSE", "type": [ "Terms of use" ], "note": "GPU 3.0 license" } ], "publication": [ { "doi": "10.1093/nar/gku1283", "pmid": "25510491", "pmcid": "PMC4357689", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "PROTEOFORMER: Deep proteome coverage through ribosome profiling and MS integration", "abstract": "An increasing amount of studies integrate mRNA sequencing data into MS-based proteomics to complement the translation product search space. However, several factors, including extensive regulation of mRNA translation and the need for threeor six-frame-translation, impede the use of mRNAseq data for the construction of a protein sequence search database.With that inmind, we developed the PROTEOFORMER tool that automatically processes data of the recently developed ribosome profiling method (sequencing of ribosome-protected mRNA fragments), resulting in genome-wide visualization of ribosome occupancy. Our tool also includes a translation initiation site calling algorithm allowing the delineation of the open reading frames (ORFs) of all translation products. A complete protein synthesisbased sequence database can thus be compiled for mass spectrometry-based identification. This approach increases the overall protein identification rates with 3% and 11% (improved and new identifications) for human and mouse, respectively, and enables proteome-wide detection of 5'-extended proteoforms, upstream ORF translation and near-cognate translation start sites. The PROTEOFORMER tool is available as a stand-alone pipeline and has been implemented in the galaxy framework for ease of use.", "date": "2015-03-11T00:00:00Z", "citationCount": 111, "authors": [ { "name": "Crappe J." }, { "name": "Ndah E." }, { "name": "Koch A." }, { "name": "Steyaert S." }, { "name": "Gawron D." }, { "name": "De Keulenaer S." }, { "name": "De Meester E." }, { "name": "De Meyer T." }, { "name": "Van Criekinge W." }, { "name": "Van Damme P." }, { "name": "Menschaert G." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1074/mcp.ra118.001218", "pmid": "31040227", "pmcid": "PMC6692777", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "PROTEOFORMER 2.0: Further developments in the ribosome profiling-assisted proteogenomic hunt for new proteoforms", "abstract": "PROTEOFORMER is a pipeline that enables the automated processing of data derived from ribosome profiling (RIBO-seq, i.e. The sequencing of ribosome-protected mRNA fragments). As such, genome-wide ribosome occupancies lead to the delineation of data-specific translation product candidates and these can improve the mass spectrometry-based identification. Since its first publication, different upgrades, new features and extensions have been added to the PROTEOFORMER pipeline. Some of the most important upgrades include P-site offset calculation during mapping, comprehensive data preexploration, the introduction of two alternative proteoform calling strategies and extended pipeline output features. These novelties are illustrated by analyzing ribosome profiling data of human HCT116 and Jurkat data. The different proteoform calling strategies are used alongside one another and in the end combined together with reference sequences from UniProt. Matching mass spectrometry data are searched against this extended search space with MaxQuant. Overall, besides annotated proteoforms, this pipeline leads to the identification and validation of different categories of new proteoforms, including translation products of up- and downstream open reading frames, 5' and 3' extended and truncated proteoforms, single amino acid variants, splice variants and translation products of so-called noncoding regions. Further, proof-of-concept is reported for the improvement of spectrum matching by including Prosit, a deep neural network strategy that adds extra fragmentation spectrum intensity features to the analysis. In the light of ribosome profiling-driven proteogenomics, it is shown that this allows validating the spectrum matches of newly identified proteoforms with elevated stringency. These updates and novel conclusions provide new insights and lessons for the ribosome profiling-based proteogenomic research field.", "date": "2019-01-01T00:00:00Z", "citationCount": 36, "authors": [ { "name": "Verbruggen S." }, { "name": "Ndah E." }, { "name": "Van Criekinge W." }, { "name": "Gessulat S." }, { "name": "Kuster B." }, { "name": "Wilhelm M." }, { "name": "Van Damme P." }, { "name": "Menschaert G." } ], "journal": "Molecular and Cellular Proteomics" } } ], "credit": [ { "name": "Steven Verbruggen", "email": "Steven.Verbruggen@UGent.be", "url": null, "orcidid": "https://orcid.org/0000-0001-9441-9539", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Documentor", "Maintainer" ], "note": "Main developer of the 2.0 version" }, { "name": "Gerben Menschaert", "email": "Gerben.Menschaert@ugent.be", "url": null, "orcidid": "https://orcid.org/0000-0002-7575-2085", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Contributor" ], "note": "PI of this project" }, { "name": "Jeroen Crappé", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-1677-9533", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "Main developer of the 1.0 version" }, { "name": "Elvis Ndah", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "Main developer of the 1.0 version" }, { "name": "Sandra Steyaert", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Contributor to the 1.0 version" }, { "name": "Alexander Koch", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Contributor to the 1.0 version" }, { "name": "Ghent University", "email": null, "url": "https://www.ugent.be/en", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null }, { "name": "BioBix", "email": null, "url": "http://www.biobix.be/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [], "note": null } ], "owner": "Katrijn.Vannerum@ugent.be", "additionDate": "2016-05-17T10:17:55Z", "lastUpdate": "2024-11-24T21:08:45.743010Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "StevenVerbruggen" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "EBprot", "description": "Perseus plugin for differential protein abundance analysis of labeling-based and label-free quantitative proteomics data", "homepage": "https://github.com/cssblab/EBprot", "biotoolsID": "ebprot", "biotoolsCURIE": "biotools:ebprot", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3634", "term": "Label-free quantification" }, { "uri": "http://edamontology.org/operation_3635", "term": "Labeled quantification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0945", "term": "Peptide identification" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Plug-in" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Windows" ], "language": [ "C++" ], "license": "Apache-2.0", "collectionID": [ "Proteomics" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/cssblab/EBprot", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/cssblab/EBprot/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/cssblab/EBprot/releases", "type": "Software package", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/cssblab/EBprot/wiki", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jproteome.8b00483", "pmid": "30411623", "pmcid": "PMC6433620", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "EBprotV2: A Perseus Plugin for Differential Protein Abundance Analysis of Labeling-Based Quantitative Proteomics Data", "abstract": "We present EBprotV2, a Perseus plugin for peptide-ratio-based differential protein abundance analysis in labeling-based proteomics experiments. The original version of EBprot models the distribution of log-transformed peptide-level ratios as a Gaussian mixture of differentially abundant proteins and nondifferentially abundant proteins and computes the probability score of differential abundance for each protein based on the reproducible magnitude of peptide ratios. However, the fully parametric model can be inflexible, and its R implementation is time-consuming for data sets containing a large number of peptides (e.g., >100000). The new tool built in the C++ language is not only faster in computation time but also equipped with a flexible semiparametric model that handles skewed ratio distributions better. We have also developed a Perseus plugin for EBprotV2 for easy access to the tool. In addition, the tool now offers a new submodule (MakeGrpData) to transform label-free peptide intensity data into peptide ratio data for group comparisons and performs differential abundance analysis using mixture modeling. This approach is especially useful when the label-free data have many missing peptide intensity data points.", "date": "2019-02-01T00:00:00Z", "citationCount": 3, "authors": [ { "name": "Koh H.W.L." }, { "name": "Zhang Y." }, { "name": "Vogel C." }, { "name": "Choi H." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1002/pmic.201400620", "pmid": "25913743", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "EBprot: Statistical analysis of labeling-based quantitative proteomics data", "abstract": "Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/)", "date": "2015-08-01T00:00:00Z", "citationCount": 10, "authors": [ { "name": "Koh H.W.L." }, { "name": "Swa H.L.F." }, { "name": "Fermin D." }, { "name": "Ler S.G." }, { "name": "Gunaratne J." }, { "name": "Choi H." } ], "journal": "Proteomics" } } ], "credit": [ { "name": "Hiromi W.L. Koh", "email": "hiromi_koh@nuhs.edu.sg", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Yunbin Zhang", "email": "yz2236@nyu.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Christine Vogel", "email": "cvogel@nyu.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Hyungwon Choi", "email": "hwchoi@nus.edu.sg", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2019-01-23T12:32:59Z", "lastUpdate": "2024-11-24T21:05:25.086214Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "InterEvDock", "description": "Ab initio protein docking based on rigid-body sampling followed by consensus scoring using physics-based and statistical potentials, including the InterEvScore function specifically developed to incorporate co-evolutionary information in docking.", "homepage": "https://mobyle.rpbs.univ-paris-diderot.fr/cgi-bin/portal.py#forms::InterEvDock2", "biotoolsID": "interevdock2", "biotoolsCURIE": "biotools:interevdock2", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3899", "term": "Protein-protein docking" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2877", "term": "Protein complex" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0477", "term": "Protein modelling" }, { "uri": "http://edamontology.org/operation_3899", "term": "Protein-protein docking" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "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_2877", "term": "Protein complex" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_2275", "term": "Molecular modelling" }, { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [], "language": [], "license": "Freeware", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock2/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gky377", "pmid": "29741647", "pmcid": "PMC6030979", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "InterEvDock2: An expanded server for protein docking using evolutionary and biological information from homology models and multimeric inputs", "abstract": "Computational protein docking is a powerful strategy to predict structures of protein-protein interactions and provides crucial insights for the functional characterization of macromolecular cross-talks. We previously developed InterEvDock, a server for ab initio protein docking based on rigid-body sampling followed by consensus scoring using physics-based and statistical potentials, including the InterEvScore function specifically developed to incorporate co-evolutionary information in docking. InterEvDock2 is a major evolution of InterEvDock which allows users to submit input sequences - not only structures - and multimeric inputs and to specify constraints for the pairwise docking process based on previous knowledge about the interaction. For this purpose, we added modules in InterEvDock2 for automatic template search and comparative modeling of the input proteins. The InterEvDock2 pipeline was benchmarked on 812 complexes for which unbound homology models of the two partners and co-evolutionary information are available in the PPI4DOCK database. InterEvDock2 identified a correct model among the top 10 consensus in 29% of these cases (compared to 15-24% for individual scoring functions) and at least one correct interface residue among 10 predicted in 91% of these cases. InterEvDock2 is thus a unique protein docking server, designed to be useful for the experimental biology community. The InterEvDock2 web interface is available at http://bioserv.rpbs.univ-Paris-diderot.fr/services/InterEvDock2/.", "date": "2018-07-02T00:00:00Z", "citationCount": 44, "authors": [ { "name": "Quignot C." }, { "name": "Rey J." }, { "name": "Yu J." }, { "name": "Tuffery P." }, { "name": "Guerois R." }, { "name": "Andreani J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkw340", "pmid": "27131368", "pmcid": "PMC4987904", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "InterEvDock: A docking server to predict the structure of protein-protein interactions using evolutionary information", "abstract": "The structural modeling of protein-protein interactions is key in understanding how cell machineries cross-talk with each other. Molecular docking simulations provide efficient means to explore how two unbound protein structures interact. InterEvDock is a server for protein docking based on a free rigidbody docking strategy. A systematic rigid-body docking search is performed using the FRODOCK program and the resulting models are re-scored with InterEvScore and SOAP-PP statistical potentials. The InterEvScore potential was specifically designed to integrate co-evolutionary information in the docking process. InterEvDock server is thus particularly well suited in case homologous sequences are available for both binding partners. The server returns 10 structures of the most likely consensus models together with 10 predicted residues most likely involved in the interface. In 91% of all complexes tested in the benchmark, at least one residue out of the 10 predicted is involved in the interface, providing useful guidelines for mutagenesis. InterEvDock is able to identify a correct model among the top10 models for 49% of the rigid-body cases with evolutionary information, making it a unique and efficient tool to explore structural interactomes under an evolutionary perspective. The InterEvDock web interface is available at http://bioserv.rpbs.univ-Paris-diderot.fr/services/InterEvDock/.", "date": "2016-01-01T00:00:00Z", "citationCount": 60, "authors": [ { "name": "Yu J." }, { "name": "Vavrusa M." }, { "name": "Andreani J." }, { "name": "Rey J." }, { "name": "Tuffery P." }, { "name": "Guerois R." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/btt260", "pmid": "23652426", "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "InterEvScore: A novel coarse-grained interface scoring function using a multi-body statistical potential coupled to evolution", "abstract": "Motivation: Structural prediction of protein interactions currently remains a challenging but fundamental goal. In particular, progress in scoring functions is critical for the efficient discrimination of near-native interfaces among large sets of decoys. Many functions have been developed using knowledge-based potentials, but few make use of multi-body interactions or evolutionary information, although multi-residue interactions are crucial for protein-protein binding and protein interfaces undergo significant selection pressure to maintain their interactions.Results: This article presents InterEvScore, a novel scoring function using a coarse-grained statistical potential including two- and three-body interactions, which provides each residue with the opportunity to contribute in its most favorable local structural environment. Combination of this potential with evolutionary information considerably improves scoring results on the 54 test cases from the widely used protein docking benchmark for which evolutionary information can be collected. We analyze how our way to include evolutionary information gradually increases the discriminative power of InterEvScore. Comparison with several previously published scoring functions (ZDOCK, ZRANK and SPIDER) shows the significant progress brought by InterEvScore. © 2013 The Author 2013. Published by Oxford University Press. All rights reserved.", "date": "2013-07-15T00:00:00Z", "citationCount": 65, "authors": [ { "name": "Andreani J." }, { "name": "Faure G." }, { "name": "Guerois R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Raphael Guerois", "email": "raphael.guerois@cea.fr", "url": null, "orcidid": "https://orcid.org/0000-0001-5294-2858", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Jessica Andreani", "email": "jessica.andreani@cea.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "reyjul", "additionDate": "2018-07-06T11:57:04Z", "lastUpdate": "2024-11-24T21:00:12.284563Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Housekeeping and Reference Transcript Atlas", "description": "Redefining human and mouse housekeeping genes and candidate reference transcripts by mining massive RNA-seq datasets.\n\nWeb-based tools to search tissue specific housekeeping genes.", "homepage": "http://www.housekeeping.unicamp.br", "biotoolsID": "Housekeeping", "biotoolsCURIE": "biotools:Housekeeping", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" }, { "uri": "http://edamontology.org/operation_3840", "term": "Multilocus sequence typing" }, { "uri": "http://edamontology.org/operation_2424", "term": "Comparison" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" }, { "uri": "http://edamontology.org/topic_0632", "term": "Probes and primers" }, { "uri": "http://edamontology.org/topic_3518", "term": "Microarray experiment" }, { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_3361", "term": "Laboratory techniques" }, { "uri": "http://edamontology.org/topic_3678", "term": "Experimental design and studies" } ], "operatingSystem": [], "language": [ "R" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://www.housekeeping.unicamp.br", "type": [ "Service", "Repository" ], "note": "Database home page" }, { "url": "https://github.com/Bidossessih/HRT_Atlas", "type": [ "Repository" ], "note": "Hrt Atlas Github" } ], "download": [], "documentation": [ { "url": "http://housekeeping.unicamp.br/?about", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkaa609", "pmid": "32663312", "pmcid": "PMC7778946", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "HRT Atlas v1.0 database: Redefining human and mouse housekeeping genes and candidate reference transcripts by mining massive RNA-seq datasets", "abstract": "Housekeeping (HK) genes are constitutively expressed genes that are required for the maintenance of basic cellular functions. Despite their importance in the calibration of gene expression, as well as the understanding of many genomic and evolutionary features, important discrepancies have been observed in studies that previously identified these genes. Here, we present Housekeeping and Reference Transcript Atlas (HRT Atlas v1.0, www.housekeeping.unicamp.br) a web-based database which addresses some of the previously observed limitations in the identification of these genes, and offers a more accurate database of human and mouse HK genes and transcripts. The database was generated by mining massive human and mouse RNA-seq data sets, including 11 281 and 507 high-quality RNA-seq samples from 52 human non-disease tissues/cells and 14 healthy tissues/cells of C57BL/6 wild type mouse, respectively. User can visualize the expression and download lists of 2158 human HK transcripts from 2176 HK genes and 3024 mouse HK transcripts from 3277 mouse HK genes. HRT Atlas also offers the most stable and suitable tissue selective candidate reference transcripts for normalization of qPCR experiments. Specific primers and predicted modifiers of gene expression for some of these HK transcripts are also proposed. HRT Atlas has also been integrated with a regulatory elements resource from Epiregio server.", "date": "2021-01-08T00:00:00Z", "citationCount": 112, "authors": [ { "name": "Hounkpe B.W." }, { "name": "Chenou F." }, { "name": "de Lima F." }, { "name": "de Paula E.V." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Bidossessi Wilfried Hounkpe", "email": "bidossessi1@live.fr", "url": null, "orcidid": "http://orcid.org/0000-0002-9992-1939", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null } ], "owner": "Pub2Tools", "additionDate": "2020-01-09T18:22:25Z", "lastUpdate": "2024-11-24T20:56:06.014004Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Fast-GBS", "description": "Fast-GBS is an analysis toolkit for genotyping-by-sequencing data. Genotyping-by-sequencing (GBS) is a rapid, flexible, low-cost, and robust genotyping method that simultaneously discovers variants and calls genotypes within a broad range of samples. These characteristics make GBS an excellent tool for many applications and research questions from conservation biology to functional genomics in both model and non-model species. Continued improvement of GBS relies on a more comprehensive understanding of data analysis, development of fast and efficient bioinformatics pipelines, accurate missing data imputation, and active post-release support.", "homepage": "https://bitbucket.org/jerlar73/fast-gbs_v2/src/master/", "biotoolsID": "fast-gbs", "biotoolsCURIE": "biotools:fast-gbs", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3557", "term": "Imputation" }, { "uri": "http://edamontology.org/operation_3196", "term": "Genotyping" }, { "uri": "http://edamontology.org/operation_3227", "term": "Variant calling" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://hub.docker.com/repository/docker/jelar5/fast-gbs_v2", "type": "Container file", "note": null, "version": null } ], "documentation": [], "publication": [ { "doi": "10.1139/gen-2020-0077", "pmid": "33006480", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Fast-gbs v2.0: An analysis toolkit for genotyping-by-sequencing data", "abstract": "Genotyping-by-sequencing (GBS) is a rapid, flexible, low-cost, and robust genotyping method that simultaneously discovers variants and calls genotypes within a broad range of samples. These characteristics make GBS an excellent tool for many applications and research questions from conservation biology to functional genomics in both model and non-model species. Continued improvement of GBS relies on a more comprehensive understanding of data analysis, development of fast and efficient bioinformatics pipelines, accurate missing data imputation, and active post-release support. Here, we present the second generation of Fast-GBS (v2.0) that offers several new options (e.g., processing paired-end reads and imputation of missing data) and features (e.g., summary statistics of genotypes) to improve the GBS data analysis process. The performance assessment analysis showed that Fast-GBS v2.0 outperformed other available analytical pipelines, such as GBS-SNP-CROP and Gb-eaSy. Fast-GBS v2.0 provides an analysis platform that can be run with different types of sequencing data, modest computational resources, and allows for missing-data imputation for various species in different contexts.", "date": "2020-01-01T00:00:00Z", "citationCount": 20, "authors": [ { "name": "Torkamaneh D." }, { "name": "Laroche J." }, { "name": "Belzile F." } ], "journal": "Genome" } }, { "doi": "10.1186/s12859-016-1431-9", "pmid": "28049422", "pmcid": "PMC5210301", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Fast-GBS: A new pipeline for the efficient and highly accurate calling of SNPs from genotyping-by-sequencing data", "abstract": "Background: Next-generation sequencing (NGS) technologies have accelerated considerably the investigation into the composition of genomes and their functions. Genotyping-by-sequencing (GBS) is a genotyping approach that makes use of NGS to rapidly and economically scan a genome. It has been shown to allow the simultaneous discovery and genotyping of thousands to millions of SNPs across a wide range of species. For most users, the main challenge in GBS is the bioinformatics analysis of the large amount of sequence information derived from sequencing GBS libraries in view of calling alleles at SNP loci. Herein we describe a new GBS bioinformatics pipeline, Fast-GBS, designed to provide highly accurate genotyping, to require modest computing resources and to offer ease of use. Results: Fast-GBS is built upon standard bioinformatics language and file formats, is capable of handling data from different sequencing platforms, is capable of detecting different kinds of variants (SNPs, MNPs, and Indels). To illustrate its performance, we called variants in three collections of samples (soybean, barley, and potato) that cover a range of different genome sizes, levels of genome complexity, and ploidy. Within these small sets of samples, we called 35 k, 32 k and 38 k SNPs for soybean, barley and potato, respectively. To assess genotype accuracy, we compared these GBS-derived SNP genotypes with independent data sets obtained from whole-genome sequencing or SNP arrays. This analysis yielded estimated accuracies of 98.7, 95.2, and 94% for soybean, barley, and potato, respectively. Conclusions: We conclude that Fast-GBS provides a highly efficient and reliable tool for calling SNPs from GBS data.", "date": "2017-01-03T00:00:00Z", "citationCount": 88, "authors": [ { "name": "Torkamaneh D." }, { "name": "Laroche J." }, { "name": "Bastien M." }, { "name": "Abed A." }, { "name": "Belzile F." } ], "journal": "BMC Bioinformatics" } } ], "credit": [], "owner": "Kigaard", "additionDate": "2021-01-18T11:25:29Z", "lastUpdate": "2024-11-24T20:39:39.982654Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PredictSNP2", "description": "A consensus classifier that combines five of the top performing tools (CADD, DANN, FATHMM, FunSeq2 and GWAVA) for the evaluation of pathogenic effect of SNPs within the human genome. The obtained results are provided together with annotations extracted from dbSNP, GenBank, Clinvar, OMIM, RegulomeDB, HaploReg, UCSC and Ensembl databases.", "homepage": "https://loschmidt.chemi.muni.cz/predictsnp2", "biotoolsID": "predictsnp2", "biotoolsCURIE": "biotools:predictsnp2", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3672", "term": "Gene functional annotation" }, { "uri": "http://edamontology.org/operation_3225", "term": "Variant classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [ { "uri": "http://edamontology.org/format_3019", "term": "GVF" }, { "uri": "http://edamontology.org/format_3016", "term": "VCF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [ { "uri": "http://edamontology.org/format_3016", "term": "VCF" }, { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] } ], "note": "VCF file containing scores and PDF file containing scores and database links", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_2533", "term": "DNA mutation" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript", "Java" ], "license": "Proprietary", "collectionID": [ "Czech Republic", "Rare Disease", "ELIXIR-CZ" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://loschmidt.chemi.muni.cz/peg/software/predictsnp2-standalone/", "type": "Downloads page", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://loschmidt.chemi.muni.cz/predictsnp2/docs/userguide.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1371/journal.pcbi.1004962", "pmid": "27224906", "pmcid": "PMC4880439", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions", "abstract": "An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools’ predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2.", "date": "2016-05-01T00:00:00Z", "citationCount": 143, "authors": [ { "name": "Bendl J." }, { "name": "Musil M." }, { "name": "Stourac J." }, { "name": "Zendulka J." }, { "name": "Damborsky J." }, { "name": "Brezovsky J." } ], "journal": "PLoS Computational Biology" } } ], "credit": [ { "name": "Jaroslav Bendl", "email": "jaroslav.bendl@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0001-9989-2720", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jan Stourac", "email": "stourac.jan@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-3139-3700", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Support" ], "note": null }, { "name": "Milos Musil", "email": "xmusil46@stud.fit.vutbr.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-9373-7930", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jan Brezovsky", "email": "brezovsky@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-9677-5078", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jiri Damborsky", "email": "1441@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-7848-8216", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Eric D. Wieben", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jaroslav Zendulka", "email": "zendulka@fit.vut.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-8718-7493", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Antonin Pavelka", "email": "99207@mail.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Loschmidt Laboratories", "email": null, "url": "https://loschmidt.chemi.muni.cz/peg/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Masaryk University, Brno, Czech Republic", "email": null, "url": "https://www.muni.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "International Centre for Clinical Research, Brno, Czech Republic", "email": null, "url": "https://www.fnusa-icrc.org/en/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Brno University of Technology, Brno, Czech Republic", "email": null, "url": "https://www.vutbr.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "ELIXIR-CZ", "email": null, "url": "https://www.elixir-czech.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Provider" ], "note": null }, { "name": "PredictSNP team", "email": "predictsnp@sci.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "European Regional Development Fund", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "European Social Fund", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Grant Agency of the Czech Republic", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Ministry of Education of the Czech Republic", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Brno University of Technology", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null } ], "owner": "Loschmidt Laboratories", "additionDate": "2016-06-30T09:32:44Z", "lastUpdate": "2024-11-24T20:23:08.475881Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "CaverDock", "description": "Performs rapid analysis of transport processes in proteins. It models the transportation of a ligand from outside environment into the protein active or binding site and vice versa. It implements a novel algorithm to produce contiguous ligand trajectory and estimation of a binding energy along the pathway. The current version uses CAVER for pathway identification and heavily modified Autodock Vina as a docking engine.", "homepage": "https://loschmidt.chemi.muni.cz/caverdock/", "biotoolsID": "caverdock", "biotoolsCURIE": "biotools:caverdock", "version": [ "1.0", "1.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0482", "term": "Protein-ligand docking" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_1463", "term": "Small molecule structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1537", "term": "Protein structure report" }, "format": [ { "uri": "http://edamontology.org/format_1957", "term": "raw" }, { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "note": "trajectory of ligand passing through protein tunnel and its energy", "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++", "Python" ], "license": "Proprietary", "collectionID": [ "CAVER", "ELIXIR-CZ" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": null, "elixirPlatform": [ "Tools" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [ { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-ubuntu-14.04.tar.gz", "type": "Binaries", "note": "v1.0, Ubuntu 14.04", "version": "1.0" }, { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-ubuntu-16.04.tar.gz", "type": "Binaries", "note": "v1.0, Ubuntu 16.04", "version": "1.0" }, { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-1.1-ubuntu-16.04.tar.xz", "type": "Binaries", "note": "v1.1, Ubuntu 16.04", "version": "1.1" }, { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-1.1-ubuntu-18.04.tar.xz", "type": "Binaries", "note": "v1.1, Ubuntu 18.04", "version": "1.1" } ], "documentation": [ { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/manual.pdf", "type": [ "User manual" ], "note": "version 1.0" }, { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/manual-1.1.pdf", "type": [ "User manual" ], "note": "version 1.1" } ], "publication": [ { "doi": "10.1093/bioinformatics/btz386", "pmid": "31077297", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "CaverDock: A molecular docking-based tool to analyse ligand transport through protein tunnels and channels", "abstract": "Motivation: Protein tunnels and channels are key transport pathways that allow ligands to pass between proteins' external and internal environments. These functionally important structural features warrant detailed attention. It is difficult to study the ligand binding and unbinding processes experimentally, while molecular dynamics simulations can be time-consuming and computationally demanding. Results: CaverDock is a new software tool for analysing the ligand passage through the biomolecules. The method uses the optimized docking algorithm of AutoDock Vina for ligand placement docking and implements a parallel heuristic algorithm to search the space of possible trajectories. The duration of the simulations takes from minutes to a few hours. Here we describe the implementation of the method and demonstrate CaverDock's usability by: (i) comparison of the results with other available tools, (ii) determination of the robustness with large ensembles of ligands and (iii) the analysis and comparison of the ligand trajectories in engineered tunnels. Thorough testing confirms that CaverDock is applicable for the fast analysis of ligand binding and unbinding in fundamental enzymology and protein engineering. Availability and implementation: User guide and binaries for Ubuntu are freely available for non-commercial use at https://loschmidt.chemi.muni.cz/caverdock/. The web implementation is available at https://loschmidt.chemi.muni.cz/caverweb/. The source code is available upon request. Supplementary information: Supplementary data are available at Bioinformatics online.", "date": "2019-12-01T00:00:00Z", "citationCount": 55, "authors": [ { "name": "Vavra O." }, { "name": "Filipovic J." }, { "name": "Plhak J." }, { "name": "Bednar D." }, { "name": "Marques S.M." }, { "name": "Brezovsky J." }, { "name": "Stourac J." }, { "name": "Matyska L." }, { "name": "Damborsky J." } ], "journal": "Bioinformatics" } }, { "doi": "10.1109/tcbb.2019.2907492", "pmid": "30932844", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "CaverDock: A Novel Method for the Fast Analysis of Ligand Transport", "abstract": "Here we present a novel method for the analysis of transport processes in proteins and its implementation called CaverDock. Our method is based on a modified molecular docking algorithm. It iteratively places the ligand along the access tunnel in such a way that the ligand movement is contiguous and the energy is minimized. The result of CaverDock calculation is a ligand trajectory and an energy profile of transport process. CaverDock uses the modified docking program Autodock Vina for molecular docking and implements a parallel heuristic algorithm for searching the space of possible trajectories. Our method lies in between the geometrical approaches and molecular dynamics simulations. Contrary to the geometrical methods, it provides an evaluation of chemical forces. However, it is far less computationally demanding and easier to set up compared to molecular dynamics simulations. CaverDock will find a broad use in the fields of computational enzymology, drug design, and protein engineering. The software is available free of charge to the academic users at https://loschmidt.chemi.muni.cz/caverdock/.", "date": "2020-09-01T00:00:00Z", "citationCount": 26, "authors": [ { "name": "Filipovic J." }, { "name": "Vavra O." }, { "name": "Plhak J." }, { "name": "Bednar D." }, { "name": "Marques S.M." }, { "name": "Brezovsky J." }, { "name": "Matyska L." }, { "name": "Damborsk J." } ], "journal": "IEEE/ACM Transactions on Computational Biology and Bioinformatics" } } ], "credit": [ { "name": "Jiri Filipovic", "email": "fila@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-5703-9673", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Ondrej Vavra", "email": "o.vavra@mail.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jan Plhak", "email": "408420@mail.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "David Bednar", "email": "222755@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-6803-0340", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Sergio Marques", "email": "smar96@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0002-6281-7505", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jan Brezovsky", "email": "brezovsky@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-9677-5078", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jan Stourac", "email": "stourac.jan@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-3139-3700", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Support" ], "note": null }, { "name": "Ludek Matyska", "email": "Ludek.Matyska@muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-6399-5453", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jiri Damborsky", "email": "1441@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-7848-8216", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Loschmidt Laboratories", "email": null, "url": "https://loschmidt.chemi.muni.cz/peg/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Masaryk University, Brno, Czech Republic", "email": null, "url": "https://www.muni.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "International Centre for Clinical Research, Brno, Czech Republic", "email": null, "url": "https://www.fnusa-icrc.org/en/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "ELIXIR-CZ", "email": null, "url": "https://www.elixir-czech.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Provider" ], "note": null }, { "name": "CaverDock team", "email": "caver@caver.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "European Commission", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Czech Science Foundation", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Brno City Municipality", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null } ], "owner": "Loschmidt Laboratories", "additionDate": "2018-04-06T08:55:47Z", "lastUpdate": "2024-11-24T20:23:05.902530Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-CZ" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PredictSNP", "description": "A consensus classifier that combines six of the top performing tools for the prediction of the effects of mutation on protein function. The obtained results are provided together with annotations extracted from the Protein Mutant Database and the UniProt database.", "homepage": "https://loschmidt.chemi.muni.cz/predictsnp1", "biotoolsID": "predictsnp", "biotoolsCURIE": "biotools:predictsnp", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "mapp", "type": "uses" }, { "biotoolsID": "nssnpanalyzer", "type": "uses" }, { "biotoolsID": "panther", "type": "uses" }, { "biotoolsID": "phd-snp", "type": "uses" }, { "biotoolsID": "polyphen", "type": "uses" }, { "biotoolsID": "polyphen-2", "type": "uses" }, { "biotoolsID": "sift", "type": "uses" }, { "biotoolsID": "snap", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0331", "term": "Variant effect prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1277", "term": "Protein features" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_2291", "term": "UniProt ID" }, "format": [] } ], "note": "Prediction of the effect of amino acid substitution on protein function", "cmd": null } ], "toolType": [ "Command-line tool", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_2885", "term": "DNA polymorphism" }, { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_3053", "term": "Genetics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript", "Java", "Python" ], "license": "Proprietary", "collectionID": [ "Czech Republic", "Rare Disease", "ELIXIR-CZ" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://loschmidt.chemi.muni.cz/predictsnp1/docs/predictsnp-1.0.tar.gz", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://loschmidt.chemi.muni.cz/predictsnp1/docs/USER_GUIDE.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1371/journal.pcbi.1003440", "pmid": "24453961", "pmcid": "PMC3894168", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations", "abstract": "Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp. © 2014 Bendl et al.", "date": "2014-01-01T00:00:00Z", "citationCount": 595, "authors": [ { "name": "Bendl J." }, { "name": "Stourac J." }, { "name": "Salanda O." }, { "name": "Pavelka A." }, { "name": "Wieben E.D." }, { "name": "Zendulka J." }, { "name": "Brezovsky J." }, { "name": "Damborsky J." } ], "journal": "PLoS Computational Biology" } } ], "credit": [ { "name": "Jaroslav Bendl", "email": "jaroslav.bendl@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0001-9989-2720", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jan Stourac", "email": "stourac.jan@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-3139-3700", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Support" ], "note": null }, { "name": "Ondrej Salanda", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jan Brezovsky", "email": "brezovsky@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-9677-5078", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jiri Damborsky", "email": "1441@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-7848-8216", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Eric D. Wieben", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jaroslav Zendulka", "email": "zendulka@fit.vut.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-8718-7493", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Antonin Pavelka", "email": "99207@mail.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Loschmidt Laboratories", "email": null, "url": "https://loschmidt.chemi.muni.cz/peg/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Masaryk University, Brno, Czech Republic", "email": null, "url": "https://www.muni.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "International Centre for Clinical Research, Brno, Czech Republic", "email": null, "url": "https://www.fnusa-icrc.org/en/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Brno University of Technology, Brno, Czech Republic", "email": null, "url": "https://www.vutbr.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Mayo Clinic, Rochester, New York, United States of America", "email": null, "url": "https://www.mayoclinic.org/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "ELIXIR-CZ", "email": null, "url": "https://www.elixir-czech.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Provider" ], "note": null }, { "name": "PredictSNP team", "email": "predictsnp@sci.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "European Regional Development Fund", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "European Social Fund", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Grant Agency of the Czech Republic", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Ministry of Education of the Czech Republic", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Brno University of Technology", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null } ], "owner": "Loschmidt Laboratories", "additionDate": "2015-11-07T20:40:08Z", "lastUpdate": "2024-11-24T20:22:54.522074Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "AraQTL", "description": "AraQTL is the A.thaliana workbench and database for eQTL analysis.\nIt allows easy access to the data of all published Arabidopsis thaliana genetical genomics experiments.", "homepage": "https://www.bioinformatics.nl/AraQTL", "biotoolsID": "araqtl", "biotoolsCURIE": "biotools:araqtl", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3232", "term": "Gene expression QTL analysis" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0282", "term": "Genetic mapping" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3360", "term": "Biomarkers" }, { "uri": "http://edamontology.org/topic_3517", "term": "GWAS study" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1111/tpj.13457", "pmid": "27995664", "pmcid": null, "type": [], "version": "1.0", "note": null, "metadata": { "title": "AraQTL – workbench and archive for systems genetics in Arabidopsis thaliana", "abstract": "Genetical genomics studies uncover genome-wide genetic interactions between genes and their transcriptional regulators. High-throughput measurement of gene expression in recombinant inbred line populations has enabled investigation of the genetic architecture of variation in gene expression. This has the potential to enrich our understanding of the molecular mechanisms affected by and underlying natural variation. Moreover, it contributes to the systems biology of natural variation, as a substantial number of experiments have resulted in a valuable amount of interconnectable phenotypic, molecular and genotypic data. A number of genetical genomics studies have been published for Arabidopsis thaliana, uncovering many expression quantitative trait loci (eQTLs). However, these complex data are not easily accessible to the plant research community, leaving most of the valuable genetic interactions unexplored as cross-analysis of these studies is a major effort. We address this problem with AraQTL (http://www.bioinformatics.nl/Ara QTL/), an easily accessible workbench and database for comparative analysis and meta-analysis of all published Arabidopsis eQTL datasets. AraQTL provides a workbench for comparing, re-using and extending upon the results of these experiments. For example, one can easily screen a physical region for specific local eQTLs that could harbour candidate genes for phenotypic QTLs, or detect gene-by-environment interactions by comparing eQTLs under different conditions.", "date": "2017-03-01T00:00:00Z", "citationCount": 15, "authors": [ { "name": "Nijveen H." }, { "name": "Ligterink W." }, { "name": "Keurentjes J.J.B." }, { "name": "Loudet O." }, { "name": "Long J." }, { "name": "Sterken M.G." }, { "name": "Prins P." }, { "name": "Hilhorst H.W." }, { "name": "de Ridder D." }, { "name": "Kammenga J.E." }, { "name": "Snoek B.L." } ], "journal": "Plant Journal" } } ], "credit": [ { "name": "Harm Nijveen", "email": "harm.nijveen@wur.nl", "url": null, "orcidid": "https://orcid.org/0000-0002-9167-4945", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Wilco Ligterink", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-0228-169X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Joost J. B. Keurentjes", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-8918-0711", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Olivier Loudet", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-3717-0137", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Jiao Long", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Mark G. Sterken", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-7119-6213", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Pjotr Prins", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Henk W. Hilhorst", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-6743-583X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Dick de Ridder", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-4944-4310", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Jan E. Kammenga", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Basten L. Snoek", "email": "basten.snoek@wur.nl", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "marieBvr", "additionDate": "2021-03-23T16:13:44Z", "lastUpdate": "2024-11-24T20:21:13.730744Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "bamtocov", "description": "Tools to extract coverage informations from BAM (and CRAM) files, based on the covtobed algorithm that supports stranded coverage and physical coverage, input from streams and uses a memory-efficient algorithm.", "homepage": "https://telatin.github.io/bamtocov/", "biotoolsID": "bamtocov", "biotoolsCURIE": "biotools:bamtocov", "version": [ "2.5.0", "2.7.0", "2.8.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0260", "term": "Sequence alignment conversion" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" }, { "uri": "http://edamontology.org/format_3462", "term": "CRAM" } ] }, { "data": { "uri": "http://edamontology.org/data_3002", "term": "Annotation track" }, "format": [ { "uri": "http://edamontology.org/format_3003", "term": "BED" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3002", "term": "Annotation track" }, "format": [ { "uri": "http://edamontology.org/format_3583", "term": "bedgraph" }, { "uri": "http://edamontology.org/format_3005", "term": "WIG" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [], "operatingSystem": [ "Linux", "Mac" ], "language": [ "C" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://telatin.github.io/bamtocov/", "type": [ "Other" ], "note": null }, { "url": "https://github.com/telatin/bamtocov", "type": [ "Repository" ], "note": null }, { "url": "https://anaconda.org/bioconda/bamtocov", "type": [ "Software catalogue" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1101/2021.11.12.466787", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": null, "note": "Preprint hosted by biorXiv", "metadata": null }, { "doi": "10.1093/bioinformatics/btac125", "pmid": "35199151", "pmcid": "PMC9048650", "type": [], "version": "1.0", "note": "Bioinformatics Application note on BamToCov", "metadata": { "title": "BamToCov: An efficient toolkit for sequence coverage calculations", "abstract": "Motivation: Many genomics applications require the computation of nucleotide coverage of a reference genome or the ability to determine how many reads map to a reference region. Results: BamToCov is a toolkit for rapid and flexible coverage computation that relies on the most memory efficient algorithm and is designed for integration in pipelines, given its ability to read alignment files from streams. The tools in the suite can process sorted BAM or CRAM files, allowing the user to extract coverage information via different filtering approaches and to save the output in different formats (BED, Wig or counts). The BamToCov algorithm can also handle strand-specific and/or physical coverage analyses.", "date": "2022-05-01T00:00:00Z", "citationCount": 11, "authors": [ { "name": "Birolo G." }, { "name": "Telatin A." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Andrea Telatin", "email": null, "url": "https://github.com/telatin", "orcidid": "https://orcid.org/0000-0001-7619-281X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Giovanni Birolo", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-0160-9312", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "telatin", "additionDate": "2022-01-25T09:42:42.478699Z", "lastUpdate": "2024-11-24T15:31:24.841052Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Cordax", "description": "The amyloid conformation can be adopted by a variety of sequences, but the precise boundaries of amyloid sequence space are still unclear. The currently charted amyloid sequence space is strongly biased towards hydrophobic, beta-sheet prone sequences that form the core of globular proteins and by Q/N/Y rich yeast prions. Here, we took advantage of the increasing amount of high-resolution structural information on amyloid cores currently available in the protein databank to implement a machine learning approach, named Cordax (https://cordax.switchlab.org) that explores amyloid sequence beyond its current boundaries.", "homepage": "https://cordax.switchlab.org", "biotoolsID": "cordax", "biotoolsCURIE": "biotools:cordax", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [ "VIB", "KU Leuven" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1038/s41467-020-17207-3", "pmid": "32620861", "pmcid": "PMC7335209", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities", "abstract": "The amyloid conformation can be adopted by a variety of sequences, but the precise boundaries of amyloid sequence space are still unclear. The currently charted amyloid sequence space is strongly biased towards hydrophobic, beta-sheet prone sequences that form the core of globular proteins and by Q/N/Y rich yeast prions. Here, we took advantage of the increasing amount of high-resolution structural information on amyloid cores currently available in the protein databank to implement a machine learning approach, named Cordax (https://cordax.switchlab.org) that explores amyloid sequence beyond its current boundaries. Clustering by t-Distributed Stochastic Neighbour Embedding (t-SNE) shows how our approach resulted in an expansion away from hydrophobic amyloid sequences towards clusters of lower aliphatic content and higher charge, or regions of helical and disordered propensities. These clusters uncouple amyloid propensity from solubility representing sequence flavours compatible with surface-exposed patches in globular proteins, functional amyloids or sequences associated to liquid-liquid phase transitions.", "date": "2020-12-01T00:00:00Z", "citationCount": 54, "authors": [ { "name": "Louros N." }, { "name": "Orlando G." }, { "name": "De Vleeschouwer M." }, { "name": "Rousseau F." }, { "name": "Schymkowitz J." } ], "journal": "Nature Communications" } } ], "credit": [ { "name": "Joost Schymkowitz", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-2020-0168", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact" ], "note": null } ], "owner": "bits@vib.be", "additionDate": "2020-12-10T17:29:48Z", "lastUpdate": "2024-11-24T15:19:34.365901Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PDBinder", "description": "PDBinder is a bioinformatic method for the prediction of small ligand binding sites in protein structures", "homepage": "http://cbm.bio.uniroma2.it/pdbinder/", "biotoolsID": "pdbinder", "biotoolsCURIE": "biotools:pdbinder", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3897", "term": "Ligand-binding site prediction" }, { "uri": "http://edamontology.org/operation_2464", "term": "Protein-protein binding site prediction" }, { "uri": "http://edamontology.org/operation_0420", "term": "Nucleic acids-binding site prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1208", "term": "protein" } ] }, { "data": { "uri": "http://edamontology.org/data_1277", "term": "Protein features" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3534", "term": "Protein binding sites" }, { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0082", "term": "Structure prediction" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/1471-2105-13-s4-s17", "pmid": "22536963", "pmcid": "PMC3434446", "type": [ "Method" ], "version": "1.0", "note": null, "metadata": { "title": "Identification of binding pockets in protein structures using a knowledge-based potential derived from local structural similarities", "abstract": "Background: The identification of ligand binding sites is a key task in the annotation of proteins with known structure but uncharacterized function. Here we describe a knowledge-based method exploiting the observation that unrelated binding sites share small structural motifs that bind the same chemical fragments irrespective of the nature of the ligand as a whole.Results: PDBinder compares a query protein against a library of binding and non-binding protein surface regions derived from the PDB. The results of the comparison are used to derive a propensity value for each residue which is correlated with the likelihood that the residue is part of a ligand binding site. The method was applied to two different problems: i) the prediction of ligand binding residues and ii) the identification of which surface cleft harbours the binding site. In both cases PDBinder performed consistently better than existing methods.PDBinder has been trained on a non-redundant set of 1356 high-quality protein-ligand complexes and tested on a set of 239 holo and apo complex pairs. We obtained an MCC of 0.313 on the holo set with a PPV of 0.413 while on the apo set we achieved an MCC of 0.271 and a PPV of 0.372.Conclusions: We show that PDBinder performs better than existing methods. The good performance on the unbound proteins is extremely important for real-world applications where the location of the binding site is unknown. Moreover, since our approach is orthogonal to those used in other programs, the PDBinder propensity value can be integrated in other algorithms further increasing the final performance. © 2012 Bianchi et al.; licensee BioMed Central Ltd.", "date": "2012-03-28T00:00:00Z", "citationCount": 16, "authors": [ { "name": "Bianchi V." }, { "name": "Gherardini P.F." }, { "name": "Helmer-Citterich M." }, { "name": "Ausiello G." } ], "journal": "BMC Bioinformatics" } } ], "credit": [], "owner": "HelmerCitterich", "additionDate": "2020-07-04T14:19:43Z", "lastUpdate": "2024-11-24T15:18:14.668324Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Plant PTM Viewer", "description": "The Plant PTM Viewer is an integrative PTM resource that comprises approximately 370 000 PTM sites for 19 types of protein modifications in plant proteins from five different species.", "homepage": "http://www.psb.ugent.be/PlantPTMViewer", "biotoolsID": "plant_ptm_viewer", "biotoolsCURIE": "biotools:plant_ptm_viewer", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3645", "term": "PTM identification" }, { "uri": "http://edamontology.org/operation_0417", "term": "PTM site prediction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0601", "term": "Protein modifications" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" } ], "operatingSystem": [], "language": [ "JavaScript" ], "license": "Not licensed", "collectionID": [ "VIB", "UGent", "BIG N2N" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Belgium" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://www.psb.ugent.be/webtools/ptm-viewer/tutorial.php", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1111/tpj.14345", "pmid": "31004550", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "The Plant PTM Viewer, a central resource for exploring plant protein modifications", "abstract": "Post-translational modifications (PTMs) of proteins are central in any kind of cellular signaling. Modern mass spectrometry technologies enable comprehensive identification and quantification of various PTMs. Given the increased numbers and types of mapped protein modifications, a database is necessary that simultaneously integrates and compares site-specific information for different PTMs, especially in plants for which the available PTM data are poorly catalogued. Here, we present the Plant PTM Viewer (http://www.psb.ugent.be/PlantPTMViewer) an integrative PTM resource that comprises approximately 370 000 PTM sites for 19 types of protein modifications in plant proteins from five different species. The Plant PTM Viewer provides the user with a protein sequence overview in which the experimentally evidenced PTMs are highlighted together with an estimate of the confidence by which the modified peptides and, if possible, the actual modification sites were identified and with functional protein domains or active site residues. The PTM sequence search tool can query PTM combinations in specific protein sequences, whereas the PTM BLAST tool searches for modified protein sequences to detect conserved PTMs in homologous sequences. Taken together, these tools help to assume the role and potential interplay of PTMs in specific proteins or within a broader systems biology context. The Plant PTM Viewer is an open repository that allows the submission of mass spectrometry-based PTM data to remain at pace with future PTM plant studies.", "date": "2019-01-01T00:00:00Z", "citationCount": 89, "authors": [ { "name": "Willems P." }, { "name": "Horne A." }, { "name": "Van Parys T." }, { "name": "Goormachtig S." }, { "name": "De Smet I." }, { "name": "Botzki A." }, { "name": "Van Breusegem F." }, { "name": "Gevaert K." } ], "journal": "Plant Journal" } } ], "credit": [ { "name": "Patrick Willems", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Provider", "Primary contact" ], "note": null }, { "name": "Thomas Van Parys", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null }, { "name": "Alison Horne", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null } ], "owner": "bits@vib.be", "additionDate": "2020-08-11T18:06:30Z", "lastUpdate": "2024-11-24T15:18:08.021106Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Beyondcell", "description": "Beyondcell is a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq data and proposing cancer-specific treatments.", "homepage": "https://github.com/cnio-bu/beyondcell", "biotoolsID": "beyondcell", "biotoolsCURIE": "biotools:beyondcell", "version": [ "2.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3223", "term": "Differential gene expression profiling" }, { "uri": "http://edamontology.org/operation_4009", "term": "Small molecule design" }, { "uri": "http://edamontology.org/operation_0313", "term": "Expression profile clustering" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3112", "term": "Gene expression matrix" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_0928", "term": "Gene expression profile" }, "format": [ { "uri": "http://edamontology.org/format_1915", "term": "Format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0951", "term": "Statistical estimate score" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3768", "term": "Clustered expression profiles" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1621", "term": "Pharmacogenomic test report" }, "format": [] } ], "note": "Beyondcell can make use of custom gene expression profiles on top of its own catalogue of drug related signatures. Beyondcell allows the user to input a GMT file containing the functional pathways/signatures of interest as well as numeric matrices containing a ranking\ncriteria such as the t-statistic or logFoldChange.", "cmd": null } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_0208", "term": "Pharmacogenomics" }, { "uri": "http://edamontology.org/topic_2640", "term": "Oncology" }, { "uri": "http://edamontology.org/topic_2229", "term": "Cell biology" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "R" ], "license": "Other", "collectionID": [ "IMPaCT-Data" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://gitlab.com/bu_cnio/beyondcell/-/issues?sort=updated_desc&state=opened", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://gitlab.com/bu_cnio/beyondcell/-/archive/master/beyondcell-master.zip", "type": "Source code", "note": "Source code for the current software version", "version": "1.3.3." }, { "url": "https://anaconda.org/bioconda/r-beyondcell", "type": "Software package", "note": "Conda package for the current software version.", "version": "1.3.3" } ], "documentation": [ { "url": "https://gitlab.com/bu_cnio/beyondcell/-/tree/master/tutorial/analysis_workflow", "type": [ "Quick start guide" ], "note": null }, { "url": "https://gitlab.com/bu_cnio/beyondcell/-/tree/master/tutorial/analysis_workflow", "type": [ "Installation instructions" ], "note": null }, { "url": "https://gitlab.com/bu_cnio/beyondcell/-/tree/master/tutorial/analysis_workflow", "type": [ "Citation instructions" ], "note": null }, { "url": "https://gitlab.com/bu_cnio/beyondcell/-/blob/master/CHANGELOG.md", "type": [ "Release notes" ], "note": null } ], "publication": [ { "doi": "10.1101/2021.04.08.438954", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": "Publication about the methodology and its application in a variety of experimental models, from cancer cell lines to human data.", "metadata": null } ], "credit": [ { "name": "Dr. Fátima Al-Shahrour", "email": "falshahrour@cnio.es", "url": null, "orcidid": "https://orcid.org/0000-0003-2373-769X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "CNIO", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "BU_CNIO", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Provider" ], "note": null } ], "owner": "tdido", "additionDate": "2021-06-14T12:59:22Z", "lastUpdate": "2024-11-24T14:48:24.542882Z", "editPermission": { "type": "group", "authors": [ "sagarcia" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "kmerAnalyzer", "description": "An alignment-free method capable of processing and counting k-mers in a reasonable time, while evaluating multiple values of the k parameter concurrently.", "homepage": "https://github.com/BiodataAnalysisGroup/kmerAnalyzer", "biotoolsID": "kmeranalyzer", "biotoolsCURIE": "biotools:kmeranalyzer", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3472", "term": "k-mer counting" }, { "uri": "http://edamontology.org/operation_3478", "term": "Phylogenetic reconstruction" }, { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_3891", "term": "Essential dynamics" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1667", "term": "E-value" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python", "R" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Greece" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.3389/fgene.2021.618170", "pmid": "34122498", "pmcid": "PMC8194296", "type": [], "version": "1.0", "note": null, "metadata": { "title": "A Computational Framework for Pattern Detection on Unaligned Sequences: An Application on SARS-CoV-2 Data", "abstract": "The exponential growth of genome sequences available has spurred research on pattern detection with the aim of extracting evolutionary signal. Traditional approaches, such as multiple sequence alignment, rely on positional homology in order to reconstruct the phylogenetic history of taxa. Yet, mining information from the plethora of biological data and delineating species on a genetic basis, still proves to be an extremely difficult problem to consider. Multiple algorithms and techniques have been developed in order to approach the problem multidimensionally. Here, we propose a computational framework for identifying potentially meaningful features based on k-mers retrieved from unaligned sequence data. Specifically, we have developed a process which makes use of unsupervised learning techniques in order to identify characteristic k-mers of the input dataset across a range of different k-values and within a reasonable time frame. We use these k-mers as features for clustering the input sequences and identifying differences between the distributions of k-mers across the dataset. The developed algorithm is part of an innovative and much promising approach both to the problem of grouping sequence data based on their inherent characteristic features, as well as for the study of changes in the distributions of k-mers, as the k-value is fluctuating within a range of values. Our framework is fully developed in Python language as an open source software licensed under the MIT License, and is freely available at https://github.com/BiodataAnalysisGroup/kmerAnalyzer.", "date": "2021-05-28T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Pechlivanis N." }, { "name": "Togkousidis A." }, { "name": "Tsagiopoulou M." }, { "name": "Sgardelis S." }, { "name": "Kappas I." }, { "name": "Psomopoulos F." } ], "journal": "Frontiers in Genetics" } } ], "credit": [ { "name": "Fotis E. Psomopoulos", "email": "fpsom@certh.gr", "url": null, "orcidid": "https://orcid.org/0000-0002-0222-4273", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Nikolaos Pechlivanis", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Anastasios Togkousidis", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Ilias Kappas", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "fpsom", "additionDate": "2021-05-17T09:02:15Z", "lastUpdate": "2024-11-24T14:48:06.612968Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Kojak", "description": "A database search algorithm for solving cross-linked peptide mass spectra.", "homepage": "https://kojak-ms.systemsbiology.net/", "biotoolsID": "kojak", "biotoolsCURIE": "biotools:kojak", "version": [ "2.0.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" } ], "operatingSystem": [ "Linux", "Windows" ], "language": [ "C++" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [ "Proteomics" ], "link": [], "download": [ { "url": "https://kojak-ms.systemsbiology.net/download.html", "type": "Downloads page", "note": null, "version": "1.0 - 2.0.0" } ], "documentation": [ { "url": "https://kojak-ms.systemsbiology.net/docs/index.html", "type": [ "Quick start guide", "Installation instructions", "User manual" ], "note": null }, { "url": "https://kojak-ms.systemsbiology.net/param/index.html", "type": [ "Command-line options" ], "note": null } ], "publication": [ { "doi": "10.1021/pr501321h", "pmid": "25812159", "pmcid": "PMC4428575", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Kojak: Efficient analysis of chemically cross-linked protein complexes", "abstract": "Protein chemical cross-linking and mass spectrometry enable the analysis of protein-protein interactions and protein topologies; however, complicated cross-linked peptide spectra require specialized algorithms to identify interacting sites. The Kojak cross-linking software application is a new, efficient approach to identify cross-linked peptides, enabling large-scale analysis of protein-protein interactions by chemical cross-linking techniques. The algorithm integrates spectral processing and scoring schemes adopted from traditional database search algorithms and can identify cross-linked peptides using many different chemical cross-linkers with or without heavy isotope labels. Kojak was used to analyze both novel and existing data sets and was compared to existing cross-linking algorithms. The algorithm provided increased cross-link identifications over existing algorithms and, equally importantly, the results in a fraction of computational time. The Kojak algorithm is open-source, cross-platform, and freely available. This software provides both existing and new cross-linking researchers alike an effective way to derive additional cross-link identifications from new or existing data sets. For new users, it provides a simple analytical resource resulting in more cross-link identifications than other methods.", "date": "2015-05-01T00:00:00Z", "citationCount": 142, "authors": [ { "name": "Hoopmann M.R." }, { "name": "Zelter A." }, { "name": "Johnson R.S." }, { "name": "Riffle M." }, { "name": "Maccoss M.J." }, { "name": "Davis T.N." }, { "name": "Moritz R.L." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1021/acs.jproteome.2c00670", "pmid": "36629399", "pmcid": "PMC10234491", "type": [ "Primary" ], "version": "2.0.0", "note": null, "metadata": { "title": "Improved Analysis of Cross-Linking Mass Spectrometry Data with Kojak 2.0, Advanced by Integration into the Trans-Proteomic Pipeline", "abstract": "Fragmentation ion spectral analysis of chemically cross-linked proteins is an established technology in the proteomics research repertoire for determining protein interactions, spatial orientation, and structure. Here we present Kojak version 2.0, a major update to the original Kojak algorithm, which was developed to identify cross-linked peptides from fragment ion spectra using a database search approach. A substantially improved algorithm with updated scoring metrics, support for cleavable cross-linkers, and identification of cross-links between 15N-labeled homomultimers are among the newest features of Kojak 2.0 presented here. Kojak 2.0 is now integrated into the Trans-Proteomic Pipeline, enabling access to dozens of additional tools within that suite. In particular, the PeptideProphet and iProphet tools for validation of cross-links improve the sensitivity and accuracy of correct cross-link identifications at user-defined thresholds. These new features improve the versatility of the algorithm, enabling its use in a wider range of experimental designs and analysis pipelines. Kojak 2.0 remains open-source and multiplatform.", "date": "2023-02-03T00:00:00Z", "citationCount": 4, "authors": [ { "name": "Hoopmann M.R." }, { "name": "Shteynberg D.D." }, { "name": "Zelter A." }, { "name": "Riffle M." }, { "name": "Lyon A.S." }, { "name": "Agard D.A." }, { "name": "Luan Q." }, { "name": "Nolen B.J." }, { "name": "MacCoss M.J." }, { "name": "Davis T.N." }, { "name": "Moritz R.L." } ], "journal": "Journal of Proteome Research" } } ], "credit": [], "owner": "mhoopmann", "additionDate": "2023-07-26T14:34:25.798022Z", "lastUpdate": "2024-11-24T14:45:40.796568Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null } ] }