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{ "count": 4148, "next": "?page=2", "previous": null, "list": [ { "name": "PathBench-MIL", "description": "PathBench-MIL is a comprehensive, flexible benchmarking/AutoML framework for multiple instance learning in histopathology. 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"40271661", "pmcid": "PMC12230652", "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Oliver Schwengers", "email": "oliver.schwengers@cb.jlug.de", "url": "https://github.com/oschwengers", "orcidid": "https://orcid.org/0000-0003-4216-2721", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "Justus Liebig University Giessen", "email": null, "url": "https://www.uni-giessen.de", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "oschwengers", "additionDate": "2021-05-08T17:25:21Z", "lastUpdate": "2026-08-07T07:24:30.787190Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-CZ", "bebatut" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "BIOSZEN", "description": "BIOSZEN is an open-source R package and modular Shiny application for reproducible analysis and visualization of experimental biological data from Excel or CSV files. It supports statistical testing, control-based normalization, replicate-aware quality control, and customizable scientific plots. \nIts microbial growth-curve module analyzes optical-density time series and automatically extracts quantitative growth parameters, including maximum specific growth rate (µMax), doubling time, lag time, maximum optical density (ODmax), time to maximum growth, area under the curve (AUC), and initial optical density (OD0). \nResults can be exported as processed datasets, statistical summaries, analysis metadata, scientific graphics, and editable PowerPoint figures.", "homepage": "https://github.com/bioszen/BIOSZEN", "biotoolsID": "bioszen", "biotoolsCURIE": "biotools:bioszen", "version": [ "2.1.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [], "output": [], "note": "Statistical analysis, control-based normalization, replicate-aware quality control, and customizable visualization of experimental biological data from Excel or CSV files.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" }, { "uri": "http://edamontology.org/operation_2945", "term": "Data analysis" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [], "output": [], "note": "Analysis and visualization of microbial optical-density time series, including extraction of uMax, max_percap_time, doubling time, lag time, ODmax, max_time, AUC, OD0, and related growth parameters.", "cmd": null } ], "toolType": [ "Desktop application", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" }, { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" } ], "operatingSystem": [ "Windows", "Mac" ], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/bioszen/BIOSZEN", "type": [ "Repository" ], "note": "Source code, example files, documentation, and development history." }, { "url": "https://github.com/bioszen/BIOSZEN/issues", "type": [ "Issue tracker" ], "note": "Bug reports, installation problems, and feature suggestions." }, { "url": "https://bioszen-test.share.connect.posit.cloud", "type": [ "Service" ], "note": "Limited online demonstration of the BIOSZEN Shiny application." } ], "download": [ { "url": "https://zenodo.org/records/18217210", "type": "Downloads page", "note": "Archived release files and permanent software record.", "version": "2.1.1" }, { "url": "https://bioszen.r-universe.dev/BIOSZEN", "type": "Software package", "note": "Installable R package for BIOSZEN 2.1.1, including access to the Shiny application.", "version": "2.1.1" } ], "documentation": [ { "url": "https://github.com/bioszen/BIOSZEN#readme", "type": [ "General", "User manual", "Quick start guide" ], "note": null }, { "url": "https://github.com/bioszen/BIOSZEN/blob/main/inst/app/www/MANUAL_EN.md", "type": [ "User manual" ], "note": "Complete BIOSZEN user manual in English." }, { "url": "https://github.com/bioszen/BIOSZEN#citation", "type": [ "Citation instructions" ], "note": null } ], "publication": [ { "doi": "10.5281/zenodo.18217210", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "all versions", "note": null, "metadata": null }, { "doi": "10.5281/zenodo.18217522", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "1.0.0", "note": null, "metadata": null } ], "credit": [ { "name": "Benjamín Szenfeld", "email": "bioszenf@gmail.com", "url": null, "orcidid": "https://orcid.org/0009-0003-4702-4149", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer", "Primary contact" ], "note": null } ], "owner": "benjamin7", "additionDate": "2026-08-04T04:51:20.841163Z", "lastUpdate": "2026-08-06T16:57:58.462807Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "RNATracker", "description": "Prediction of mRNA subcellular localization using deep recurrent neural networks | RNATracker is a deep learning approach to learn mRNA subcellular localization patterns and to infer its outcome. It operates on the cDNA of the longest isoformic protein-coding transcript of a gene with or without its corresponding secondary structure annnotations. The learning targets are fractions/percentage of the transcripts being localized to a fixed set of subcellular compartments of interest", "homepage": "https://www.github.com/HarveyYan/RNATracker", "biotoolsID": "RNATracker", "biotoolsCURIE": "biotools:RNATracker", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2489", "term": "Subcellular localisation prediction" }, { "uri": "http://edamontology.org/operation_0443", "term": "trans-regulatory element prediction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" } ], "operatingSystem": [], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/BIOINFORMATICS/BTZ337", "pmid": "31510698", "pmcid": "PMC6612824", "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Mathieu Blanchette", "email": "blanchem@cs.mcgill.ca", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "Pub2Tools", "additionDate": "2019-11-14T19:50:03Z", "lastUpdate": "2026-08-02T05:55:43.612294Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "CSP-Analyzer", "description": "A novel Machine Learning-based application for automated analysis of two-dimensional NMR spectra in NMR fragment-based screening.\n\nA fast and efficient multi-spectrum anlayzer for 2-D NMR Fragment Screening based on SMOTE-ENN machine-learning discriminator. - rubbs14/CSP-Analyzer.", "homepage": "https://github.com/rubbs14/CSP-Analyzer/releases/tag/v1.0", "biotoolsID": "csp-analyzer", "biotoolsCURIE": "biotools:csp-analyzer", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3215", "term": "Peak detection" }, { "uri": "http://edamontology.org/operation_3891", "term": "Essential dynamics" }, { "uri": "http://edamontology.org/operation_3860", "term": "Spectrum calculation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0593", "term": "NMR" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_3336", "term": "Drug discovery" } ], "operatingSystem": [], "language": [ "C#", "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1016/J.CSBJ.2020.02.015", "pmid": "32257044", "pmcid": "PMC7096735", "type": [], "version": null, "note": null, "metadata": { "title": "Introducing the CSP Analyzer: A novel Machine Learning-based application for automated analysis of two-dimensional NMR spectra in NMR fragment-based screening", "abstract": "© 2020 The AuthorsNMR-based screening, especially fragment-based drug discovery is a valuable approach in early-stage drug discovery. Monitoring fragment-binding in protein-detected 2D NMR experiments requires analysis of hundreds of spectra to detect chemical shift perturbations (CSPs) in the presence of ligands screened. Computational tools are available that simplify the tracking of CSPs in 2D NMR spectra. However, to the best of our knowledge, an efficient automated tool for the assessment and binning of multiple spectra for ligand binding has not yet been described. We present a novel and fast approach for analysis of multiple 2D HSQC spectra based on machine-learning-driven statistical discrimination. The CSP Analyzer features a C# frontend interfaced to a Python ML classifier. The software allows rapid evaluation of 2D screening data from large number of spectra, reducing user-introduced bias in the evaluation. The CSP Analyzer software package is available on GitHub https://github.com/rubbs14/CSP-Analyzer/releases/tag/v1.0 under the GPL license 3.0 and is free to use for academic and commercial uses.", "date": "2020-01-01T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Fino R." }, { "name": "Byrne R." }, { "name": "Softley C.A." }, { "name": "Sattler M." }, { "name": "Schneider G." }, { "name": "Popowicz G.M." } ], "journal": "Computational and Structural Biotechnology Journal" } } ], "credit": [ { "name": "G.M. Popowicz", "email": "grzegorz.popowicz@helmholtz-muenchen.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "roberto", "additionDate": "2021-01-18T08:45:59Z", "lastUpdate": "2026-07-27T14:35:54.373975Z", "editPermission": { "type": "group", "authors": [ "roberto" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "ClustVis", "description": "Web tool which allows users to upload their own data and easily create Principal Component Analysis (PCA) plots and heatmaps. Data can be uploaded as a file or by copy-pasteing it to the text box.", "homepage": "http://biit.cs.ut.ee/clustvis", "biotoolsID": "clustvis", "biotoolsCURIE": "biotools:clustvis", "version": [ "1" ], "otherID": [ { "value": "RRID:SCR_017133", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0313", "term": "Gene expression clustering" }, { "uri": "http://edamontology.org/operation_2942", "term": "Treemap visualisation" }, { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" }, { "uri": "http://edamontology.org/operation_2939", "term": "Principal component plotting" }, { "uri": "http://edamontology.org/operation_0531", "term": "Heat map generation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3111", "term": "Processed microarray data" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3033", "term": "Matrix format" } ] }, { "data": { "uri": "http://edamontology.org/data_3113", "term": "Sample annotation" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3033", "term": "Matrix format" } ] }, { "data": { "uri": "http://edamontology.org/data_0928", "term": "Gene expression profile" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3033", "term": "Matrix format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1636", "term": "Heat map" }, "format": [ { "uri": "http://edamontology.org/format_3466", "term": "EPS" }, { "uri": "http://edamontology.org/format_3604", "term": "SVG" }, { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3466", "term": "EPS" }, { "uri": "http://edamontology.org/format_3604", "term": "SVG" }, { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [ "Elixir-EE" ], "maturity": null, "cost": "Free of charge", "accessibility": null, "elixirPlatform": [ "Tools" ], "elixirNode": [ "Estonia" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/taunometsalu/ClustVis", "type": [ "Repository" ], "note": "A code repository in github." } ], "download": [ { "url": "https://hub.docker.com/r/taunometsalu/clustvis/", "type": "Container file", "note": "Docker image", "version": null } ], "documentation": [ { "url": "https://biit.cs.ut.ee/clustvis/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkv468", "pmid": "25969447", "pmcid": "PMC4489295", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "ClustVis: A web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap", "abstract": "The Principal Component Analysis (PCA) is a widely used method of reducing the dimensionality of highdimensional data, often followed by visualizing two of the components on the scatterplot. Although widely used, the method is lacking an easy-to-use web interface that scientists with little programming skills could use to make plots of their own data. The same applies to creating heatmaps: it is possible to add conditional formatting for Excel cells to show colored heatmaps, but for more advanced features such as clustering and experimental annotations, more sophisticated analysis tools have to be used. We present a web tool called ClustVis that aims to have an intuitive user interface. Users can upload data from a simple delimited text file that can be created in a spreadsheet program. It is possible to modify data processing methods and the final appearance of the PCA and heatmap plots by using drop-down menus, text boxes, sliders etc. Appropriate defaults are given to reduce the time needed by the user to specify input parameters. As an output, users can download PCA plot and heatmap in one of the preferred file formats. This web server is freely available at http://biit.cs.ut.ee/clustvis/.", "date": "2015-01-01T00:00:00Z", "citationCount": 2504, "authors": [ { "name": "Metsalu T." }, { "name": "Vilo J." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "ELIXIR-EE", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Tauno Metsalu", "email": "tauno.metsalu@ut.ee", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": null, "email": "biit.support@ut.ee", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "user.1781877465", "additionDate": "2015-01-22T11:13:24Z", "lastUpdate": "2026-07-21T21:16:04.483218Z", "editPermission": { "type": "group", "authors": [ "may.kay", "sssjh" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MOODS", "description": "A suite of algorithms for matching position weight matrices (PWM) against DNA sequences. It features advanced matrix matching algorithms implemented in C++ that can be used to scan hundreds of matrices against chromosome-sized sequences in few seconds. MOODS can also process high-order PWMs with dependencies between adjacent positions and sequence variants such as SNPs, insertions and deletions.", "homepage": "https://www.cs.helsinki.fi/group/pssmfind/", "biotoolsID": "moods", "biotoolsCURIE": "biotools:moods", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0239", "term": "Sequence motif recognition" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_0102", "term": "Mapping" }, { "uri": "http://edamontology.org/topic_0157", "term": "Sequence composition, complexity and repeats" } ], "operatingSystem": [ "Linux" ], "language": [ "C++", "Python" ], "license": "GPL-3.0", "collectionID": [ "Animal and Crop Genomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/jhkorhonen/MOODS", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/jhkorhonen/MOODS/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/jhkorhonen/MOODS/wiki/Getting-started", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1109/tcbb.2009.35", "pmid": "21071798", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Finding significant matches of position weight matrices in linear time", "abstract": "Position weight matrices are an important method for modeling signals or motifs in biological sequences, both in DNA and protein contexts. In this paper, we present fast algorithms for the problem of finding significant matches of such matrices. Our algorithms are of the online type, and they generalize classical multipattern matching, filtering, and superalphabet techniques of combinatorial string matching to the problem of weight matrix matching. Several variants of the algorithms are developed, including multiple matrix extensions that perform the search for several matrices in one scan through the sequence database. Experimental performance evaluation is provided to compare the new techniques against each other as well as against some other online and index-based algorithms proposed in the literature. Compared to the brute-force O(mn) approach, our solutions can be faster by a factor that is proportional to the matrix length m. Our multiple-matrix filtration algorithm had the best performance in the experiments. On a current PC, this algorithm finds significant matches (p = 0.0001) of the 123 JASPAR matrices in the human genome in about 18 minutes. © 2011 IEEE.", "date": "2011-01-01T00:00:00Z", "citationCount": 24, "authors": [ { "name": "Pizzi C." }, { "name": "Rastas P." }, { "name": "Ukkonen E." } ], "journal": "IEEE/ACM Transactions on Computational Biology and Bioinformatics" } }, { "doi": "10.1093/bioinformatics/btw683", "pmid": "28011774", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Fast motif matching revisited: High-order PWMs, SNPs and indels", "abstract": "Motivation: While the position weight matrix (PWM) is the most popular model for sequence motifs, there is growing evidence of the usefulness of more advanced models such as first-order Markov representations, and such models are also becoming available in well-known motif databases. There has been lots of research of how to learn these models from training data but the problem of predicting putative sites of the learned motifs by matching the model against new sequences has been given less attention. Moreover, motif site analysis is often concerned about how different variants in the sequence affect the sites. So far, though, the corresponding efficient software tools for motif matching have been lacking. Results: We develop fast motif matching algorithms for the aforementioned tasks. First, we formalize a framework based on high-order position weight matrices for generic representation of motif models with dinucleotide or general q-mer dependencies, and adapt fast PWM matching algorithms to the high-order PWM framework. Second, we show how to incorporate different types of sequence variants, such as SNPs and indels, and their combined effects into efficient PWM matching workflows. Benchmark results show that our algorithms perform well in practice on genome-sized sequence sets and are for multiple motif search much faster than the basic sliding window algorithm.", "date": "2017-02-15T00:00:00Z", "citationCount": 23, "authors": [ { "name": "Korhonen J.H." }, { "name": "Palin K." }, { "name": "Taipale J." }, { "name": "Ukkonen E." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bioinformatics/btp554", "pmid": "19773334", "pmcid": "PMC2778336", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "MOODS: Fast search for position weight matrix matches in DNA sequences", "abstract": "Summary: MOODS (MOtif Occurrence Detection Suite) is a software package for matching position weight matrices against DNA sequences. MOODS implements state-of-the-art online matching algorithms, achieving considerably faster scanning speed than with a simple brute-force search. MOODS is written in C++, with bindings for the popular BioPerl and Biopython toolkits. It can easily be adapted for different purposes and integrated into existing workflows. It can also be used as a C++ library. © The Author(s) 2009. Published by Oxford University Press.", "date": "2009-09-22T00:00:00Z", "citationCount": 116, "authors": [ { "name": "Korhonen J." }, { "name": "Martinmaki P." }, { "name": "Pizzi C." }, { "name": "Rastas P." }, { "name": "Ukkonen E." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": null, "email": "janne.h.korhonen@aalto.fi", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Bamboo", "additionDate": "2017-08-20T15:58:06Z", "lastUpdate": "2026-07-21T21:15:59.464608Z", "editPermission": { "type": "group", "authors": [ "animalandcropgenomics" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Pangolin", "description": "Pangolin is a deep-learning based method for predicting splice site strengths (for details, see Zeng and Li, Genome Biology 2022). It is available as a command-line tool that can be run on a VCF or CSV file containing variants of interest; Pangolin will predict changes in splice site strength due to each variant, and return a file of the same format. Pangolin's models can also be used with custom sequences.", "homepage": "https://github.com/tkzeng/Pangolin", "biotoolsID": "pangolin", "biotoolsCURIE": "biotools:pangolin", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0433", "term": "Splice site prediction" }, { "uri": "http://edamontology.org/operation_0232", "term": "Sequence merging" }, { "uri": "http://edamontology.org/operation_0264", "term": "Alternative splicing prediction" }, { "uri": "http://edamontology.org/operation_3196", "term": "Genotyping" }, { "uri": "http://edamontology.org/operation_3225", "term": "Variant classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [ { "uri": "http://edamontology.org/format_3016", "term": "VCF" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3320", "term": "RNA splicing" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" }, { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_3676", "term": "Exome sequencing" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/s13059-022-02664-4", "pmid": "35449021", "pmcid": "PMC9022248", "type": [], "version": null, "note": null, "metadata": { "title": "Predicting RNA splicing from DNA sequence using Pangolin", "abstract": "Recent progress in deep learning has greatly improved the prediction of RNA splicing from DNA sequence. Here, we present Pangolin, a deep learning model to predict splice site strength in multiple tissues. Pangolin outperforms state-of-the-art methods for predicting RNA splicing on a variety of prediction tasks. Pangolin improves prediction of the impact of genetic variants on RNA splicing, including common, rare, and lineage-specific genetic variation. In addition, Pangolin identifies loss-of-function mutations with high accuracy and recall, particularly for mutations that are not missense or nonsense, demonstrating remarkable potential for identifying pathogenic variants.", "date": "2022-12-01T00:00:00Z", "citationCount": 52, "authors": [ { "name": "Zeng T." }, { "name": "Li Y.I." } ], "journal": "Genome Biology" } } ], "credit": [ { "name": "Yang I Li", "email": "yangili1@uchicago.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-0736-251X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Tony Zeng", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "Jennifer", "additionDate": "2022-07-26T10:11:09.660345Z", "lastUpdate": "2026-07-21T21:15:53.848510Z", "editPermission": { "type": "group", "authors": [ "xiangjun_zhao" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "kMetaShot", "description": "The application of 2nd and 3rd generation High Throughput Sequencing (HTS) technologies has deeply reshaped experimental method to investigate microbial communities and obtain a taxonomic and functional profile of the invetigated community. Shotgun Metagenomics allow to quickly obtain a representation of microorganisms genomes characterizing a particular environment. In order to obtain a fast e reliable taxonomic classification of microorganisms genomes we present kMetaShot, an alignment-free taxonomic classifier based on k-mer/minimizer counting.", "homepage": "https://github.com/gdefazio/kMetaShot", "biotoolsID": "kMetaShot", "biotoolsCURIE": "biotools:kMetaShot", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Italy" ], "elixirCommunity": [ "Marine Metagenomics" ], "link": [], "download": [], "documentation": [ { "url": "https://github.com/gdefazio/kMetaShot", "type": [ "Other" ], "note": null } ], "publication": [ { "doi": "10.1093/bib/bbae680", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Giuseppe Defazio", "email": "giuseppe.defazio@uniba.it", "url": "https://persone.ict.uniba.it/rubrica/@@cerca?advanced_search=False&sort_on=&SearchableText=defazio", "orcidid": "https://orcid.org/0000-0002-9356-5224", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "Post-Doc Researcher at University of Bari" } ], "owner": "gdefazio", "additionDate": "2024-02-29T15:44:00.705364Z", "lastUpdate": "2026-07-17T09:37:14.810675Z", "editPermission": { "type": "group", "authors": [ "bfosso", "gpesole" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "mtag", "description": "mtag is a Python-based command line tool for jointly analyzing multiple sets of GWAS summary statistics as described by Turley et. al. (2018). It can also be used as a tool to meta-analyze GWAS results.", "homepage": "https://github.com/JonJala/mtag", "biotoolsID": "mtag", "biotoolsCURIE": "biotools:mtag", "version": [ "0.9.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3209", "term": "Genome comparison" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2478", "term": "Nucleic acid sequence analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3517", "term": "GWAS study" } ], "operatingSystem": [], "language": [ "Perl", "Python", "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/JonJala/mtag/wiki", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/s41588-017-0009-4", "pmid": "29292387", "pmcid": "PMC5805593", "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "johangustafsson", "additionDate": "2026-07-17T04:45:01.899451Z", "lastUpdate": "2026-07-17T04:45:01.902519Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "mothur", "description": "Open-source, platform-independent, community-supported software for describing and comparing microbial communities", "homepage": "http://mothur.org/", "biotoolsID": "mothur", "biotoolsCURIE": "biotools:mothur", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3200", "term": "DNA barcoding" }, { "uri": "http://edamontology.org/operation_3218", "term": "Sequencing quality control" }, { "uri": "http://edamontology.org/operation_0291", "term": "Sequence clustering" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_3921", "term": "Sequence read processing" }, { "uri": "http://edamontology.org/operation_0324", "term": "Phylogenetic analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Suite" ], "topic": [ { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" }, { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_0084", "term": "Phylogeny" } ], "operatingSystem": [], "language": [ "C++" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/mothur/mothur", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/mothur", "type": [ "Other", "Repository" ], "note": "mothur GitHub organization" } ], "download": [], "documentation": [ { "url": "http://mothur.org/wiki/mothur_manual/", "type": [ "User manual" ], "note": null }, { "url": "http://mothur.org/wiki/", "type": [ "Other" ], "note": "mothur Wiki page" } ], "publication": [ { "doi": "10.1128/aem.01541-09", "pmid": "19801464", "pmcid": "PMC2786419", "type": [], "version": null, "note": null, "metadata": { "title": "Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities", "abstract": "Mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the α and β diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer. Copyright © 2009, American Society for Microbiology. All Rights Reserved.", "date": "2009-12-01T00:00:00Z", "citationCount": 16666, "authors": [ { "name": "Schloss P.D." }, { "name": "Westcott S.L." }, { "name": "Ryabin T." }, { "name": "Hall J.R." }, { "name": "Hartmann M." }, { "name": "Hollister E.B." }, { "name": "Lesniewski R.A." }, { "name": "Oakley B.B." }, { "name": "Parks D.H." }, { "name": "Robinson C.J." }, { "name": "Sahl J.W." }, { "name": "Stres B." }, { "name": "Thallinger G.G." }, { "name": "Van Horn D.J." }, { "name": "Weber C.F." } ], "journal": "Applied and Environmental Microbiology" } } ], "credit": [], "owner": "admin", "additionDate": "2022-02-24T00:12:40.833213Z", "lastUpdate": "2026-07-10T02:41:43.627271Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "thromboSeq", "description": "thromboSeq is a bioinformatics tool designed for the analysis of thrombosis-related sequencing data, providing functionalities for variant calling, annotation, and functional interpretation. It streamlines the processing of high-throughput sequencing data to identify genetic variants associated with thrombotic disorders.", "homepage": "https://github.com/MyronBest/thromboSeq_source_code", "biotoolsID": "thromboseq", "biotoolsCURIE": "biotools:thromboseq", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_1812", "term": "Data parsing" }, { "uri": "http://edamontology.org/operation_0314", "term": "Gene expression profiling" }, { "uri": "http://edamontology.org/operation_3218", "term": "Sequencing quality control" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_2058", "term": "Gene expression report format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2955", "term": "Sequence report" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [], "topic": [], "operatingSystem": [], "language": [ "Shell", "R", "Perl" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.3390/cancers13184644", "pmid": "34572871", "pmcid": "PMC8468408", "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2026-07-08T15:57:08.302197Z", "lastUpdate": "2026-07-08T15:57:08.307883Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "qam", "description": "qam is a Python library and command-line tool to compute 3D surface-distances for evaluating liver ablation/tumor completeness based on segmentation images.", "homepage": "https://github.com/artorg-unibe-ch/qam", "biotoolsID": "qam", "biotoolsCURIE": "biotools:qam", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3443", "term": "Image analysis" }, { "uri": "http://edamontology.org/operation_3438", "term": "Calculation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library", "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3384", "term": "Medical imaging" } ], "operatingSystem": [], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.3389/fonc.2021.623098", "pmid": "33777768", "pmcid": "PMC7988092", "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2026-07-08T11:30:16.311175Z", "lastUpdate": "2026-07-08T11:30:16.314189Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PanAbyss", "description": "PanAbyss is a tool for exploring and visualizing pangenome graphs. It allows users to search for and display regions of a pangenome using coordinates on a reference individual or based on annotations. 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"RhizoVision Explorer is free and open-source software developed for estimating root traits from images acquired from a flatbed scanner or camera. 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Root characteristics like length, diameter and volume are critical to measure to understand plant and soil functions. RhizoVision Explorer is an open-source software designed to enable researchers interested in roots by providing an easy-To-use interface, fast image processing and reliable measurements. The default broken roots mode is intended for roots sampled from pots and soil cores, washed and typically scanned on a flatbed scanner, and provides measurements like length, diameter and volume. The optional whole root mode for complete root systems or root crowns provides additional measurements such as angles, root depth and convex hull. Both modes support providing measurements grouped by defined diameter ranges, the inclusion of multiple regions of interest and batch analysis. RhizoVision Explorer was successfully validated against ground truth data using a new copper wire image set. In comparison, the current reference software, the commercial WinRhizo™, drastically underestimated volume when wires of different diameters were in the same image. Additionally, measurements were compared with WinRhizo™ and IJ_Rhizo using a simulated root image set, showing general agreement in software measurements, except for root volume. Finally, scanned root image sets acquired in different labs for the crop, herbaceous and tree species were used to compare results from RhizoVision Explorer with WinRhizo™. The two software showed general agreement, except that WinRhizo™ substantially underestimated root volume relative to RhizoVision Explorer. In the current context of rapidly growing interest in root science, RhizoVision Explorer intends to become a reference software, improve the overall accuracy and replicability of root trait measurements and provide a foundation for collaborative improvement and reliable access to all.", "date": "2021-12-01T00:00:00Z", "citationCount": 130, "authors": [ { "name": "Seethepalli A." }, { "name": "Dhakal K." }, { "name": "Griffiths M." }, { "name": "Guo H." }, { "name": "Freschet G.T." }, { "name": "York L.M." } ], "journal": "AoB PLANTS" } } ], "credit": [ { "name": "Larry M. York", "email": "lmyork@noble.org", "url": null, "orcidid": "https://orcid.org/0000-0002-1995-9479", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Kigaard", "additionDate": "2021-11-29T10:31:42.544157Z", "lastUpdate": "2026-03-17T09:34:03.454691Z", "editPermission": { "type": "group", "authors": [ "RDKing" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Freezing-Point", "description": "Freezing-Point is a user-friendly open-source software for the automated analysis of freezing behavior in rodents. Based on recorded videos or pose estimation files. An adaptive, data-driven algorithm automatically determines freezing detection thresholds, reducing subjective bias while preserving user oversight. Freezing-Point adopts a user-oriented design centered on a graphical interface that provides continuous visual access to original data, processing steps and analysis results. 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Computes normal modes, fluctuation profiles, inter-residue correlations, conformational overlap analysis and vector field representations. Structural amino acid profiles, and normal mode characteristics describing protein motion, visualized in plots and decorated structure visualizations. White space delimited tabular data for normal modes and the provided plots", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2487", "term": "Protein structure comparison" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0886", "term": "Structure alignment" }, "format": [ { "uri": "http://edamontology.org/format_2200", "term": "FASTA-like (text)" } ] }, { "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_2884", "term": "Plot" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_0889", "term": "Structural profile" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "Performs comparative analysis of the normal modes of protein structures. 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. Non specialists can easily and rapidly evaluate the degree of flexibility of multi-domain protein assemblies and characterize the large amplitude movements of their domains. © 2005 Hollup et al; licensee BioMed Central Ltd.", "date": "2005-03-11T00:00:00Z", "citationCount": 105, "authors": [ { "name": "Hollup S.M." }, { "name": "Salensminde G." }, { "name": "Reuter N." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Nathalie Reuter", "email": "Nathalie.Reuter@uib.no", "url": "http://www.cbu.uib.no/reuter/", "orcidid": "https://orcid.org/0000-0002-3649-7675", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer" ], "note": null }, { "name": "Sandhya P Tiwari", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-0747-3826", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Kidane M Tekle", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Tristan Cragnolini", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Svenn H Grindhaug", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Lars Skjærven", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Gisle Salensminde", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Edvin Fuglebakk", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Siv M Hollup", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Department of Molecular Biology, University of Bergen, Norway", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Computational Biology Unit, Department of Informatics, University of Bergen, Norway", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "UiB", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "UiB", "additionDate": "2016-03-17T13:51:10Z", "lastUpdate": "2026-03-11T08:56:55.566213Z", "editPermission": { "type": "group", "authors": [ "eca008", "korbinib" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BioMercator", "description": "BioMercator is a software that provides a complete set of algorithms and visualization tool covering all steps required to perform QTL meta-analysis, graphical representation of large datasets. User may import sequence and genome annotations datasets within the software in order to display functional annotation related to QTL and meta-QTL.", "homepage": "https://sourcesup.renater.fr/projects/biomercator", "biotoolsID": "BioMercator", "biotoolsCURIE": "biotools:BioMercator", "version": [ "4.2.3" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0282", "term": "Genetic mapping" }, { "uri": "http://edamontology.org/operation_2944", "term": "Physical mapping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1860", "term": "QTL map" }, "format": [ { "uri": "http://edamontology.org/format_2332", "term": "XML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_1288", "term": "Genome map" }, "format": [ { "uri": "http://edamontology.org/format_1975", "term": "GFF3" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_3055", "term": "Quantitative genetics" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://sourcesup.renater.fr/frs/?group_id=2301", "type": "Binaries", "note": null, "version": "4.2.3" } ], "documentation": [], "publication": [ { "doi": "10.1093/bioinformatics/bth230", "pmid": "15059820", "pmcid": null, "type": [], "version": "3", "note": null, "metadata": { "title": "BioMercator: Integrating genetic maps and QTL towards discovery of candidate genes", "abstract": "Summary: Breeding programs face the challenge of integrating information from genomics and from quantitative trait loci (QTL) analysis in order to identify genomic sequences controlling the variation of important traits. Despite the development of integrative databases, building a consensus map of genes, QTL and other loci gathered from multiple maps remains a manual and tedious task. Nevertheless, this is a critical step to reveal co-locations between genes and QTL. Another important matter is to determine whether QTL linked to same traits or related ones is detected in independent experiments and located in the same region, and represents a single locus or not. Statistical tools such as meta-analysis can be used to answer this question. BioMercator has been developed to automate map compilation and QTL meta-analysis, and to visualize co-locations between genes and QTL through a graphical interface. © Oxford University Press 2004; all rights reserved.", "date": "2004-09-22T00:00:00Z", "citationCount": 382, "authors": [ { "name": "Arcade A." }, { "name": "Labourdette A." }, { "name": "Falque M." }, { "name": "Mangin B." }, { "name": "Chardon F." }, { "name": "Charcosset A." }, { "name": "Joets J." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "admin", "additionDate": "2019-09-27T09:58:46Z", "lastUpdate": "2026-03-11T08:56:54.859634Z", "editPermission": { "type": "group", "authors": [ "b.guerra01" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BigSeqKit", "description": "The Next Generation Sequencing (NGS) raw data are stored in FASTA and FASTQ text-based file formats. Common operations on FASTA/Q files include searching, filtering, sampling, deduplication and sorting, among others. We can find several tools in the literature for FASTA/Q file manipulation but none of them are well fitted for large files of tens of GB (likely TBs in the near future) since mostly they are based on sequential processing. The exception is seqkit that allows some routines to use a few threads but, in any case, the scalability is very limited. To deal with this issue, we introduce BigSeqKit, a parallel toolkit to manipulate FASTA/Q files at scale with speed and scalability at its core. BigSeqKit takes advantage of an HPC-Big Data framework (IgnisHPC) to parallelize and optimize the commands included in seqkit. In this way, in most cases it is from tens to hundreds of times faster than other state-of-the-art tools such as seqkit, samtools and pyfastx.", "homepage": "https://github.com/citiususc/BigSeqKit", "biotoolsID": "bigseqkit", "biotoolsCURIE": "biotools:bigseqkit", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3192", "term": "Sequence trimming" }, { "uri": "http://edamontology.org/operation_0372", "term": "DNA transcription" }, { "uri": "http://edamontology.org/operation_0371", "term": "DNA translation" }, { "uri": "http://edamontology.org/operation_0233", "term": "Sequence conversion" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "cesarpomar", "additionDate": "2023-05-22T15:10:32.141196Z", "lastUpdate": "2026-03-01T11:28:15.208151Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PLAST", "description": "PLAST is a heuristical method to search for highest scoring local alignments between a DNA sequence query and a graphical pangenome. It takes as input a plain DNA sequence and a pangenome which may either be a set of (multiple) FASTA or FASTQ files or a sequence graph constructed by the tool Bifrost. It then outputs statistically meaningful (gapped) alignments in the style of the NCBI BLAST standard output format. Alignments are calculated based on a \"seed-and-extend approach\" while traversing the sequence graph. Biologically meaningful alignments are filtered by using an alignment statistic explicitly developed for sequence-to-graph alignments involving graphical pangenomes.", "homepage": "https://github.com/tischulz1/plast", "biotoolsID": "pangenome-blast", "biotoolsCURIE": "biotools:pangenome-blast", "version": [ "0.0.1-0.2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0495", "term": "Local alignment" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1211", "term": "unambiguous pure nucleotide" } ] }, { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_3975", "term": "GFA 1" }, { "uri": "http://edamontology.org/format_2333", "term": "Binary format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_1333", "term": "BLAST results" } ] } ], "note": "In order to search for alignments within the pangenome graph, \nA pangenome graph used to search for alignments consists of (1) a file in GFA format containing all sequences of the graph, (2) a binary file produced by the tool itself or the software \"Bifrost\" and (3) a program-specific index data structure in binary format.", "cmd": "PLAST Search -i pangenomeGraphCommonFilePrefix -q fileContainingOneQueryPerLine" }, { "operation": [ { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0850", "term": "Sequence set" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" }, { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0850", "term": "Sequence set" }, "format": [ { "uri": "http://edamontology.org/format_3975", "term": "GFA 1" }, { "uri": "http://edamontology.org/format_2333", "term": "Binary format" } ] } ], "note": "If a pangenome graph already exists and only an index has to be built, FASTA/FASTQ files are not needed.", "cmd": "PLAST Build -i pangenomeGraphCommonFilePrefix -R *.fasta" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0797", "term": "Comparative genomics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [ "C++" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://gitlab.ub.uni-bielefeld.de/gi/plast", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/tischulz1/plast", "type": [ "Mirror" ], "note": null } ], "download": [], "documentation": [ { "url": "https://gitlab.ub.uni-bielefeld.de/gi/plast/-/blob/master/README.md", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btab077", "pmid": "33532821", "pmcid": "PMC8388040", "type": [ "Primary", "Method", "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "Detecting high-scoring local alignments in pangenome graphs", "abstract": "Motivation: Increasing amounts of individual genomes sequenced per species motivate the usage of pangenomic approaches. Pangenomes may be represented as graphical structures, e.g. compacted colored de Bruijn graphs, which offer a low memory usage and facilitate reference-free sequence comparisons. While sequence-to-graph mapping to graphical pangenomes has been studied for some time, no local alignment search tool in the vein of BLAST has been proposed yet. Results: We present a new heuristic method to find maximum scoring local alignments of a DNA query sequence to a pangenome represented as a compacted colored de Bruijn graph. Our approach additionally allows a comparison of similarity among sequences within the pangenome. We show that local alignment scores follow an exponential-tail distribution similar to BLAST scores, and we discuss how to estimate its parameters to separate local alignments representing sequence homology from spurious findings. An implementation of our method is presented, and its performance and usability are shown. Our approach scales sublinearly in running time and memory usage with respect to the number of genomes under consideration. This is an advantage over classical methods that do not make use of sequence similarity within the pangenome.", "date": "2021-08-15T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Schulz T." }, { "name": "Wittler R." }, { "name": "Rahmann S." }, { "name": "Hach F." }, { "name": "Stoye J." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Bielefeld University", "email": null, "url": "https://www.uni-bielefeld.de/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Genome Informatics", "email": null, "url": "https://gi.cebitec.uni-bielefeld.de/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Tizian Schulz", "email": "plast-service@cebitec.uni-bielefeld.de", "url": null, "orcidid": "https://orcid.org/0000-0003-0744-7078", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "tizian", "additionDate": "2021-05-06T06:18:52Z", "lastUpdate": "2026-02-26T11:22:02.485629Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ESIprot", "description": "Charge state determination and molecular weight calculation for low resolution electrospray ionization data.", "homepage": "https://nube-gran.de/esiprot", "biotoolsID": "esiprot", "biotoolsCURIE": "biotools:esiprot", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0398", "term": "Protein molecular weight calculation" }, { "uri": "http://edamontology.org/operation_2929", "term": "Protein fragment weight comparison" }, { "uri": "http://edamontology.org/operation_3629", "term": "Deisotoping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0944", "term": "Peptide mass fingerprint" }, "format": [ { "uri": "http://edamontology.org/format_3245", "term": "Mass spectrometry data format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0944", "term": "Peptide mass fingerprint" }, "format": [ { "uri": "http://edamontology.org/format_3245", "term": "Mass spectrometry data format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [ "ms-utils", "Proteomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://www.bioprocess.org/esiprot/esiprot_form.php", "type": [ "Mirror" ], "note": null }, { "url": "http://ms-utils.org", "type": [ "Software catalogue" ], "note": null } ], "download": [ { "url": "http://www.bioprocess.org/esiprot/esiprot.zip", "type": "Source code", "note": null, "version": null }, { "url": "http://www.bioprocess.org/esiprot/esiprot.zip", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "http://www.lababi.bioprocess.org/index.php/lababi-software/84-esiprot", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1002/rcm.4384", "pmid": "20049890", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "ESIprot: A universal tool for charge state determination and molecular weight calculation of proteins from electrospray ionization mass spectrometry data", "abstract": "Electrospray ionization (ESI) ion trap mass spectrometers with relatively low resolution are frequently used for the analysis of natural products and peptides. Although ESI spectra of multiply charged protein molecules also can be measured on this type of devices, only average spectra are produced for the majority of naturally occurring proteins. Evaluating such ESI protein spectra would provide valuable information about the native state of investigated proteins. However, no suitable and freely available software could be found which allows the charge state determination and molecular weight calculation of single proteins from average ESI-MS data. Therefore, an algorithm based on standard deviation optimization (scatter minimization) was implemented for the analysis of protein ESI-MS data. The resulting software ESIprot was tested with ESI-MS data of six intact reference proteins between 12.4 and 66.7kDa. In all cases, the correct charge states could be determined. The obtained absolute mass errors were in a range between -0.2 and 1.2Da, the relative errors below 30ppm. The possible mass accuracy allows for valid conclusions about the actual condition of proteins. Moreover, the ESIprot algorithm demonstrates an extraordinary robustness and allows spectral interpretation from as little as two peaks, given sufficient quality of the provided m/z data, without the necessity for peak intensity data. ESIprot is independent from the raw data format and the computer platform, making it a versatile tool for mass spectrometrists. The program code was released under the open-source GPLv3 license to support future developments of mass spectrometry software. © 2010 John Wiley & Sons, Ltd.", "date": "2010-01-01T00:00:00Z", "citationCount": 75, "authors": [ { "name": "Winkler R." } ], "journal": "Rapid Communications in Mass Spectrometry" } } ], "credit": [ { "name": "Robert Winkler", "email": "robert.winkler@ira.cinvestav.mx", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null }, { "name": null, "email": "webmaster@ms-utils.org", "url": "http://ms-utils.org", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Documentor" ], "note": null } ], "owner": "msutils_import", "additionDate": "2017-01-17T14:50:59Z", "lastUpdate": "2026-02-24T10:43:29.547210Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "kilpejen" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "kollaR", "description": "kollaR is an open-source R library for eye-tracking analysis and visualization, offering functions for event detection, AOI-based analyses, and algorithm comparison. 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