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{ "count": 33203, "next": "?page=2", "previous": null, "list": [ { "name": "ancseq", "description": "A local command-line tool for ancestral sequence reconstruction with gap-state inference using IQ-TREE. 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The program is completely general for any ligand and can also be used to show other types of interaction in proteins and nucleic acids. It was designed to facilitate the rapid inspection of many enzyme complexes, but has found many other applications. © 1995 Oxford University Press.", "date": "1995-02-01T00:00:00Z", "citationCount": 4892, "authors": [ { "name": "Wallace A.C." }, { "name": "Laskowski R.A." }, { "name": "Thornton J.M." } ], "journal": "Protein Engineering, Design and Selection" } }, { "doi": "10.1021/ci200227u", "pmid": "21919503", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "LigPlot+: Multiple ligand-protein interaction diagrams for drug discovery", "abstract": "We describe a graphical system for automatically generating multiple 2D diagrams of ligand-protein interactions from 3D coordinates. The diagrams portray the hydrogen-bond interaction patterns and hydrophobic contacts between the ligand(s) and the main-chain or side-chain elements of the protein. The system is able to plot, in the same orientation, related sets of ligand-protein interactions. This facilitates popular research tasks, such as analyzing a series of small molecules binding to the same protein target, a single ligand binding to homologous proteins, or the completely general case where both protein and ligand change. © 2011 American Chemical Society.", "date": "2011-10-24T00:00:00Z", "citationCount": 4265, "authors": [ { "name": "Laskowski R.A." }, { "name": "Swindells M.B." } ], "journal": "Journal of Chemical Information and Modeling" } } ], "credit": [ { "name": "Roman Laskowski", "email": "roman@ebi.ac.uk", "url": "http://www.ebi.ac.uk/~roman/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "elnaz", "additionDate": "2017-08-03T18:48:05Z", "lastUpdate": "2026-07-21T21:18:36.432397Z", "editPermission": { "type": "group", "authors": [ "arjun", "sergitobara", "elnaz" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "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": 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[], "credit": [ { "name": "Ivan Brezani", "email": null, "url": "https://www.mathworks.com/matlabcentral/profile/2241235-ivan-brezani", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "zsmag19", "additionDate": "2021-05-05T11:09:42Z", "lastUpdate": "2026-07-21T21:16:00.781732Z", "editPermission": { "type": "group", "authors": [ "Verena_H" ] }, "validated": 0, "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": "Supernova", "description": "Supernova is a software package for de novo assembly from Chromium Linked-Reads that are made from a single whole-genome library from an individual DNA source. A key feature of Supernova is that it creates diploid assemblies, thus separately representing maternal and paternal chromosomes over very long distances. Almost all other methods instead merge homologous chromosomes into single incorrect 'consensus' sequences. Supernova is the only practical method for creating diploid assemblies of large genomes.", "homepage": "https://support.10xgenomics.com/de-novo-assembly/software/overview/latest/welcome", "biotoolsID": "supernova", "biotoolsCURIE": "biotools:supernova", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3933", "term": "Demultiplexing" }, { "uri": "http://edamontology.org/operation_0524", "term": "De-novo assembly" }, { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" }, { "uri": "http://edamontology.org/operation_3192", "term": "Sequence trimming" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Suite", "Workflow", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" }, { "uri": "http://edamontology.org/topic_3673", "term": "Whole genome sequencing" }, { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" } ], "operatingSystem": [ "Linux" ], "language": [], "license": "Proprietary", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://support.10xgenomics.com/de-novo-assembly/software/downloads/latest", "type": "Downloads page", "note": null, "version": null } ], "documentation": [ { "url": "https://support.10xgenomics.com/de-novo-assembly/software/pipelines/latest/installation", "type": [ "Installation instructions" ], "note": null }, { "url": "https://support.10xgenomics.com/de-novo-assembly/software/release-notes/2-1", "type": [ "Release notes" ], "note": null } ], "publication": [ { "doi": "10.1101/gr.214874.116", "pmid": "28381613", "pmcid": "PMC5411770", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Direct determination of diploid genome sequences", "abstract": "Determining the genome sequence of an organism is challenging, yet fundamental to understanding its biology. Over the past decade, thousands of human genomes have been sequenced, contributing deeply to biomedical research. In the vast majority of cases, these have been analyzed by aligning sequence reads to a single reference genome, biasing the resulting analyses, and in general, failing to capture sequences novel to a given genome. Some de novo assemblies have been constructed free of reference bias, but nearly all were constructed by merging homologous loci into single \"consensus\" sequences, generally absent from nature. These assemblies do not correctly represent the diploid biology of an individual. In exactly two cases, true diploid de novo assemblies have been made, at great expense. One was generated using Sanger sequencing, and one using thousands of clone pools. Here, we demonstrate a straightforward and low-cost method for creating true diploid de novo assemblies. We make a single library from ~1 ng of high molecular weight DNA, using the 10x Genomics microfluidic platform to partition the genome. We applied this technique to seven human samples, generating low-cost HiSeq X data, then assembled these using a new \"pushbutton\" algorithm, Supernova. Each computation took 2 d on a single server. Each yielded contigs longer than 100 kb, phase blocks longer than 2.5 Mb, and scaffolds longer than 15 Mb. Our method provides a scalable capability for determining the actual diploid genome sequence in a sample, opening the door to new approaches in genomic biology and medicine.", "date": "2017-05-01T00:00:00Z", "citationCount": 519, "authors": [ { "name": "Weisenfeld N.I." }, { "name": "Kumar V." }, { "name": "Shah P." }, { "name": "Church D.M." }, { "name": "Jaffe D.B." } ], "journal": "Genome Research" } } ], "credit": [ { "name": "David B. Jaffe", "email": "david.jaffe@10xgenomics.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "10x Genomics", "email": "support@10xgenomics.com", "url": "https://10xgenomics.com", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null } ], "owner": "user.1783928322", "additionDate": "2021-05-27T09:17:19Z", "lastUpdate": "2026-07-21T21:15:54.674089Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "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": "ITSoneWB", "description": "ITSoneWB (ITSone WorkBench) is a Galaxy-based bioinformatic environment where comprehensive and high-quality reference data are connected with established pipelines and new tools in an automated and easy-to-use service targeted at global taxonomic analysis of eukaryotic communities based on Internal Transcribed Spacer 1 variants high-throughput sequencing.", "homepage": "http://itsonewb.cloud.ba.infn.it/galaxy", "biotoolsID": "itsonewb", "biotoolsCURIE": "biotools:itsonewb", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" }, { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "bfosso", "additionDate": "2021-03-24T10:36:29Z", "lastUpdate": "2026-07-21T21:15:52.818219Z", "editPermission": { "type": "group", "authors": [ "bfosso" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ASAP", "description": "ASAP (Assemble Species by Automatic Partitioning) is a method to build species partitions from single locus sequence alignments.\nASAP is the implementation of a hierarchical clustering algorithm that only uses pairwise genetic distances, avoiding the computational burden of phylogenetic reconstruction. Importantly, ASAP proposes species partitions ranked by a new scoring system that uses no biological prior insight of intraspecific diversity.", "homepage": "https://bioinfo.mnhn.fr/abi/public/asap", "biotoolsID": "asap-assemble", "biotoolsCURIE": "biotools:asap-assemble", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3478", "term": "Phylogenetic reconstruction" }, { "uri": "http://edamontology.org/operation_3200", "term": "DNA barcoding" }, { "uri": "http://edamontology.org/operation_0310", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/operation_3359", "term": "Splitting" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" }, { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://bioinfo.mnhn.fr/abi/public/asap/help_asap.html", "type": [ "General" ], "note": null }, { "url": "https://bioinfo.mnhn.fr/abi/public/asap/FAQ_asap.html", "type": [ "FAQ" ], "note": null } ], "publication": [ { "doi": "10.1111/1755-0998.13281", "pmid": "33058550", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "ASAP: assemble species by automatic partitioning", "abstract": "© 2020 John Wiley & Sons LtdHere, we describe Assemble Species by Automatic Partitioning (ASAP), a new method to build species partitions from single locus sequence alignments (i.e., barcode data sets). ASAP is efficient enough to split data sets as large 104 sequences into putative species in several minutes. Although grounded in evolutionary theory, ASAP is the implementation of a hierarchical clustering algorithm that only uses pairwise genetic distances, avoiding the computational burden of phylogenetic reconstruction. Importantly, ASAP proposes species partitions ranked by a new scoring system that uses no biological prior insight of intraspecific diversity. ASAP is a stand-alone program that can be used either through a graphical web-interface or that can be downloaded and compiled for local usage. We have assessed its power along with three others programs (ABGD, PTP and GMYC) on 10 real COI barcode data sets representing various degrees of challenge (from small and easy cases to large and complicated data sets). We also used Monte-Carlo simulations of a multispecies coalescent framework to assess the strengths and weaknesses of ASAP and the other programs. Through these analyses, we demonstrate that ASAP has the potential to become a major tool for taxonomists as it proposes rapidly in a full graphical exploratory interface relevant species hypothesis as a first step of the integrative taxonomy process.", "date": "2021-02-01T00:00:00Z", "citationCount": 15, "authors": [ { "name": "Puillandre N." }, { "name": "Brouillet S." }, { "name": "Achaz G." } ], "journal": "Molecular Ecology Resources" } } ], "credit": [ { "name": "Nicolas Puillandre", "email": "puillandre@mnhn.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "Kigaard", "additionDate": "2021-01-18T11:19:37Z", "lastUpdate": "2026-07-21T21:15:51.417139Z", "editPermission": { "type": "group", "authors": [ "arkamukherjee", "keqing" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "JGI Genome Portal", "description": "The JGI Genome Portal provides a unified access point to all JGI genomic databases and analytical tools. A user can find all DOE JGI sequencing projects and their status, search for and download assemblies and annotations of sequenced genomes, and interactively explore those genomes and compare them with other sequenced microbes, fungi, plants or metagenomes using specialized systems tailored to each particular class of organisms.", "homepage": "http://genome.jgi.doe.gov/", "biotoolsID": "jgi_genome_portal", "biotoolsCURIE": "biotools:jgi_genome_portal", "version": [], "otherID": [ { "value": "RRID:SCR_002383", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0525", "term": "Genome assembly" }, { "uri": "http://edamontology.org/operation_0310", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/operation_3216", "term": "Scaffolding" }, { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://jgi.doe.gov/user-program-info/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkr947", "pmid": "22110030", "pmcid": "PMC3245080", "type": [], "version": null, "note": null, "metadata": { "title": "The Genome Portal of the Department of Energy Joint Genome Institute", "abstract": "The Department of Energy (DOE) Joint Genome Institute (JGI) is a national user facility with massive-scale DNA sequencing and analysis capabilities dedicated to advancing genomics for bioenergy and environmental applications. Beyond generating tens of trillions of DNA bases annually, the Institute develops and maintains data management systems and specialized analytical capabilities to manage and interpret complex genomic data sets, and to enable an expanding community of users around the world to analyze these data in different contexts over the web. The JGI Genome Portal (http://genome.jgi.doe. gov) provides a unified access point to all JGI genomic databases and analytical tools. A user can find all DOE JGI sequencing projects and their status, search for and download assemblies and annotations of sequenced genomes, and interactively explore those genomes and compare them with other sequenced microbes, fungi, plants or metagenomes using specialized systems tailored to each particular class of organisms. We describe here the general organization of the Genome Portal and the most recent addition, MycoCosm (http://jgi.doe.gov/ fungi), a new integrated fungal genomics resource. © The Author(s) 2011.", "date": "2012-01-01T00:00:00Z", "citationCount": 386, "authors": [ { "name": "Grigoriev I.V." }, { "name": "Nordberg H." }, { "name": "Shabalov I." }, { "name": "Aerts A." }, { "name": "Cantor M." }, { "name": "Goodstein D." }, { "name": "Kuo A." }, { "name": "Minovitsky S." }, { "name": "Nikitin R." }, { "name": "Ohm R.A." }, { "name": "Otillar R." }, { "name": "Poliakov A." }, { "name": "Ratnere I." }, { "name": "Riley R." }, { "name": "Smirnova T." }, { "name": "Rokhsar D." }, { "name": "Dubchak I." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "I.V. Grigoriev", "email": "ivgrigoriev@lbl.gov", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-EE", "additionDate": "2017-03-30T23:00:28Z", "lastUpdate": "2026-07-21T21:15:50.005041Z", "editPermission": { "type": "group", "authors": [ "ursula" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ChimeraX", "description": "Structure visualization for researchers, educators, and developers.\n\nTutorials can be viewed in any browser, but those with click-to-execute links should be viewed from within ChimeraX for the links to work. To view a web page from within ChimeraX, start ChimeraX and use the command open URL (substituting in the actual URL), or navigate here using the ChimeraX menu: Help... Tutorials.\n\nUCSF ChimeraX is the next-generation molecular visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera.", "homepage": "https://www.rbvi.ucsf.edu/chimerax", "biotoolsID": "chimerax", "biotoolsCURIE": "biotools:chimerax", "version": [], "otherID": [], "relation": [ { "biotoolsID": "artiax", "type": "includes" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_0387", "term": "Molecular surface calculation" }, { "uri": "http://edamontology.org/operation_0480", "term": "Side chain modelling" }, { "uri": "http://edamontology.org/operation_0478", "term": "Molecular docking" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3382", "term": "Imaging" }, { "uri": "http://edamontology.org/topic_2275", "term": "Molecular modelling" }, { "uri": "http://edamontology.org/topic_0605", "term": "Informatics" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_3794", "term": "RNA immunoprecipitation" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.rbvi.ucsf.edu/chimerax/gallery.html", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [ { "url": "https://www.rbvi.ucsf.edu/chimerax/features.html", "type": [ "General" ], "note": null }, { "url": "https://www.rbvi.ucsf.edu/chimerax/tutorials.html", "type": [ "Training material" ], "note": null } ], "publication": [ { "doi": "10.1002/pro.3943", "pmid": "32881101", "pmcid": "PMC7737788", "type": [], "version": null, "note": null, "metadata": { "title": "UCSF ChimeraX: Structure visualization for researchers, educators, and developers", "abstract": "UCSF ChimeraX is the next-generation interactive visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera. ChimeraX brings (a) significant performance and graphics enhancements; (b) new implementations of Chimera's most highly used tools, many with further improvements; (c) several entirely new analysis features; (d) support for new areas such as virtual reality, light-sheet microscopy, and medical imaging data; (e) major ease-of-use advances, including toolbars with icons to perform actions with a single click, basic “undo” capabilities, and more logical and consistent commands; and (f) an app store for researchers to contribute new tools. ChimeraX includes full user documentation and is free for noncommercial use, with downloads available for Windows, Linux, and macOS from https://www.rbvi.ucsf.edu/chimerax.", "date": "2021-01-01T00:00:00Z", "citationCount": 4079, "authors": [ { "name": "Pettersen E.F." }, { "name": "Goddard T.D." }, { "name": "Huang C.C." }, { "name": "Meng E.C." }, { "name": "Couch G.S." }, { "name": "Croll T.I." }, { "name": "Morris J.H." }, { "name": "Ferrin T.E." } ], "journal": "Protein Science" } }, { "doi": "10.1002/pro.3235", "pmid": "28710774", "pmcid": "PMC5734306", "type": [], "version": null, "note": null, "metadata": { "title": "UCSF ChimeraX: Meeting modern challenges in visualization and analysis", "abstract": "UCSF ChimeraX is next-generation software for the visualization and analysis of molecular structures, density maps, 3D microscopy, and associated data. It addresses challenges in the size, scope, and disparate types of data attendant with cutting-edge experimental methods, while providing advanced options for high-quality rendering (interactive ambient occlusion, reliable molecular surface calculations, etc.) and professional approaches to software design and distribution. This article highlights some specific advances in the areas of visualization and usability, performance, and extensibility. ChimeraX is free for noncommercial use and is available from http://www.rbvi.ucsf.edu/chimerax/ for Windows, Mac, and Linux.", "date": "2018-01-01T00:00:00Z", "citationCount": 2746, "authors": [ { "name": "Goddard T.D." }, { "name": "Huang C.C." }, { "name": "Meng E.C." }, { "name": "Pettersen E.F." }, { "name": "Couch G.S." }, { "name": "Morris J.H." }, { "name": "Ferrin T.E." } ], "journal": "Protein Science" } } ], "credit": [ { "name": "Thomas E. Ferrin", "email": "tef@cgl.ucsf.edu", "url": null, "orcidid": "https://orcid.org/0000-0001-6227-0637", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "zsmag19", "additionDate": "2021-01-18T10:54:08Z", "lastUpdate": "2026-07-21T21:15:49.368925Z", "editPermission": { "type": "group", "authors": [ "sergitobara", "Puja123" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "CyTargetLinker", "description": "A flexible solution for network extension in Cytoscape | The CyTargetLinker app extends biological networks with regulatory interactions, for example miRNA-target, TF-target or drug-target interactions | CyTargetLinker website and tutorials | CyTargetLinker - Extend your biological networks in Cytoscape", "homepage": "https://cytargetlinker.github.io/", "biotoolsID": "CyTargetLinker", "biotoolsCURIE": "biotools:CyTargetLinker", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3439", "term": "Pathway or network prediction" }, { "uri": "http://edamontology.org/operation_0277", "term": "Pathway or network comparison" }, { "uri": "http://edamontology.org/operation_1781", "term": "Gene regulatory network analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" } ], "operatingSystem": [], "language": [ "Java" ], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://apps.cytoscape.org/apps/cytargetlinker", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/CyTargetLinker/cytargetlinker/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://cytargetlinker.github.io/pages/citation", "type": [ "Citation instructions" ], "note": null }, { "url": "https://cytargetlinker.github.io/pages/docs", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.12688/F1000RESEARCH.14613.2", "pmid": "31489175", "pmcid": "PMC6707396", "type": [], "version": null, "note": null, "metadata": { "title": "Cytargetlinker app update: A flexible solution for network extension in cytoscape", "abstract": "© 2019 Kutmon M et al.Here, we present an update of the open-source CyTargetLinker app for Cytoscape (http://apps.cytoscape.org/apps/cytargetlinker) that introduces new automation features. CyTargetLinker provides a simple interface to extend networks with links to relevant data and/or knowledge extracted from so-called linksets. The linksets are provided on the CyTargetLinker website (https://cytargetlinker.github.io/) or can be custom-made for specific use cases. The new automation feature enables users to programmatically execute the app’s functionality in Cytoscape (command line tool) and with external tools (e.g. R, Jupyter, Python, etc). This allows users to share their analysis workflows and therefore increase repeatability and reproducibility. Three use cases demonstrate automated workflows, combinations with other Cytoscape apps and core Cytoscape functionality. We first extend a protein-protein interaction network created with the stringApp, with compound-target interactions and disease-gene annotations. In the second use case, we created a workflow to load differentially expressed genes from an experimental dataset and extend it with gene-pathway associations. Lastly, we chose an example outside the biological domain and used CyTargetLinker to create an author-article-journal network for the five authors of this manuscript using a two-step extension mechanism. With 400 downloads per month in the last year and nearly 20,000 downloads in total, CyTargetLinker shows the adoption and relevance of the app in the field of network biology. In August 2019, the original publication was cited in 83 articles demonstrating the applicability in biomedical research.", "date": "2019-01-01T00:00:00Z", "citationCount": 11, "authors": [ { "name": "Kutmon M." }, { "name": "Ehrhart F." }, { "name": "Willighagen E.L." }, { "name": "Evelo C.T." }, { "name": "Coort S.L." } ], "journal": "F1000Research" } }, { "doi": "10.1371/journal.pone.0082160", "pmid": "24340000", "pmcid": "PMC3855388", "type": [], "version": null, "note": null, "metadata": { "title": "Cytargetlinker: A Cytoscape app to integrate regulatory interactions in network analysis", "abstract": "Introduction: The high complexity and dynamic nature of the regulation of gene expression, protein synthesis, and protein activity pose a challenge to fully understand the cellular machinery. By deciphering the role of important players, including transcription factors, microRNAs, or small molecules, a better understanding of key regulatory processes can be obtained. Various databases contain information on the interactions of regulators with their targets for different organisms, data recently being extended with the results of the ENCODE (Encyclopedia of DNA Elements) project. A systems biology approach integrating our understanding on different regulators is essential in interpreting the regulation of molecular biological processes. Implementation: We developed CyTargetLinker (http://projects.bigcat.unimaas.nl/cytargetlinker) a Cytoscape app, for integrating regulatory interactions in network analysis. Recently we released CyTargetLinker as one of the first apps for Cytoscape 3. It provides a user-friendly and flexible interface to extend biological networks with regulatory interactions, such as microRNA-target, transcription factor-target and/or drug-target. Importantly, CyTargetLinker employs identifier mapping to combine various interaction data resources that use different types of identifiers. Results: Three case studies demonstrate the strength and broad applicability of CyTargetLinker, (i) extending a mouse molecular interaction network, containing genes linked to diabetes mellitus, with validated and predicted microRNAs, (ii) enriching a molecular interaction network, containing DNA repair genes, with ENCODE transcription factor and (iii) building a regulatory meta-network in which a biological process is extended with information on transcription factor, microRNA and drug regulation. Conclusions: CyTargetLinker provides a simple and extensible framework for biologists and bioinformaticians to integrate different regulatory interactions into their network analysis approaches. Visualization options enable biological interpretation of complex regulatory networks in a graphical way. Importantly the incorporation of our tool into the Cytoscape framework allows the application of CyTargetLinker in combination with a wide variety of other apps for state-ofthe- art network analysis. Copyright: © 2013 Kutmon et al.", "date": "2013-12-05T00:00:00Z", "citationCount": 83, "authors": [ { "name": "Kutmon M." }, { "name": "Kelder T." }, { "name": "Mandaviya P." }, { "name": "Evelo C.T.A." }, { "name": "Coort S.L." } ], "journal": "PLoS ONE" } } ], "credit": [ { "name": "Martina Kutmon", "email": "martina.kutmon@maastrichtuniversity.nl", "url": null, "orcidid": "https://orcid.org/0000-0002-7699-8191", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2019-11-14T18:10:12Z", "lastUpdate": "2026-07-21T21:15:46.757924Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "DRAM", "description": "Distilled and Refined Annotation of Metabolism: A tool for the annotation and curation of function for microbial and viral genomes", "homepage": "https://github.com/WrightonLabCSU/DRAM", "biotoolsID": "dram", "biotoolsCURIE": "biotools:dram", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3672", "term": "Gene functional annotation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3071", "term": "Biological databases" }, { "uri": "http://edamontology.org/topic_3321", "term": "Molecular genetics" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/WrightonLabCSU/DRAM", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/WrightonLabCSU/DRAM/wiki", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkaa621", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2024-02-09T12:34:05.629565Z", "lastUpdate": "2026-07-21T21:15:45.619297Z", "editPermission": { "type": "group", "authors": [ "clsiguret" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ArrayAnalysis", "description": "ArrayAnalysis is a web-based application for transcriptomic data analysis. 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