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{ "count": 726, "next": "?page=2", "previous": null, "list": [ { "name": "rnaspades", "description": "Pipeline for de novo transcriptome assembly from RNA-Seq.", "homepage": "http://cab.spbu.ru/software/spades/", "biotoolsID": "rnaspades", "biotoolsCURIE": "biotools:rnaspades", "version": [ "3.9.0" ], "otherID": [ { "value": "RRID:SCR_016992", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0524", "term": "De-novo assembly" }, { "uri": "http://edamontology.org/operation_3258", "term": "Transcriptome assembly" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] }, { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] }, { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0863", "term": "Sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" }, { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "galaxyPasteur", "SPAdes" ], "maturity": "Mature", "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/fmareuil/rnaspades/rnaspades/3.9.0", "type": [ "Galaxy service" ], "note": null } ], "download": [], "documentation": [ { "url": "http://spades.bioinf.spbau.ru/release3.11.1/rnaspades_manual.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1089/cmb.2012.0021", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "SPAdes: A new genome assembly algorithm and its applications to single-cell sequencing", "abstract": "The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online (http://bioinf.spbau.ru/spades). It is distributed as open source software. © Copyright 2012, Mary Ann Liebert, Inc.", "date": "2012-05-01T00:00:00Z", "citationCount": 15962, "authors": [ { "name": "Bankevich A." }, { "name": "Nurk S." }, { "name": "Antipov D." }, { "name": "Gurevich A.A." }, { "name": "Dvorkin M." }, { "name": "Kulikov A.S." }, { "name": "Lesin V.M." }, { "name": "Nikolenko S.I." }, { "name": "Pham S." }, { "name": "Prjibelski A.D." }, { "name": "Pyshkin A.V." }, { "name": "Sirotkin A.V." }, { "name": "Vyahhi N." }, { "name": "Tesler G." }, { "name": "Alekseyev M.A." }, { "name": "Pevzner P.A." } ], "journal": "Journal of Computational Biology" } }, { "doi": "10.1093/nar/gkw343", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update", "abstract": "High-throughput data production technologies, particularly ‘next-generation’ DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. In this report we highlight recently added features enabling biomedical analyses on a large scale.", "date": "2016-07-08T00:00:00Z", "citationCount": 1348, "authors": [ { "name": "Afgan E." }, { "name": "Baker D." }, { "name": "van den Beek M." }, { "name": "Blankenberg D." }, { "name": "Bouvier D." }, { "name": "Cech M." }, { "name": "Chilton J." }, { "name": "Clements D." }, { "name": "Coraor N." }, { "name": "Eberhard C." }, { "name": "Gruning B." }, { "name": "Guerler A." }, { "name": "Hillman-Jackson J." }, { "name": "Kuster G.V." }, { "name": "Rasche E." }, { "name": "Soranzo N." }, { "name": "Turaga N." }, { "name": "Taylor J." }, { "name": "Nekrutenko A." }, { "name": "Goecks J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.7490/f1000research.1114334.1", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Galaxy Support Team", "email": "galaxy@pasteur.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "hmenager", "additionDate": "2016-12-19T14:26:53Z", "lastUpdate": "2024-03-08T15:29:01.478112Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "M2aia", "description": "M²aia (MSI applications for interactive analysis in MITK) is a software tool enabling interactive signal processing and visualisation of mass spectrometry imaging (MSI) datasets. M²aia extends the open source Medical Imaging and Interaction Toolkit (MITK; https://www.mitk.org) and provides powerful methods that the MSI community can adopt, exploit and improve further. In it’s current state, it is designed to enable multi-modal 2D registration and 3D MSI reconstruction.", "homepage": "https://m2aia.github.io/m2aia", "biotoolsID": "m2aia", "biotoolsCURIE": "biotools:m2aia", "version": [], "otherID": [ { "value": "RRID:SCR_019324", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2409", "term": "Data handling" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" }, { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] }, { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3551", "term": "nrrd" }, { "uri": "http://edamontology.org/format_3727", "term": "OME-TIFF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" }, { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] }, { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3551", "term": "nrrd" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Desktop application", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Linux", "Windows" ], "language": [ "C++" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/m2aia/m2aia", "type": [ "Issue tracker", "Repository" ], "note": null }, { "url": "https://www.mitk.org", "type": [ "Other" ], "note": null } ], "download": [ { "url": "https://m2aia.de", "type": "Downloads page", "note": null, "version": null } ], "documentation": [ { "url": "https://www.protocols.io/view/supporting-protocol-for-use-case-1-dimensionality-brw4m7gw", "type": [ "Training material" ], "note": "Supporting protocol for use-case 1: Dimensionality reduction in \"M2aia - Interactive, fast and memory efficient analysis of 2D and 3D multi-modal mass spectrometry imaging data\"" }, { "url": "https://www.protocols.io/view/supporting-protocol-for-use-case-2-multi-modal-3d-bvq8n5zw", "type": [ "Training material" ], "note": "Supporting protocol for use-case 2: Multi-modal 3D image reconstruction in \"M2aia - Interactive, fast and memory efficient analysis of 2D and 3D multi-modal mass spectrometry imaging data\"" }, { "url": "https://www.protocols.io/view/supporting-protocol-for-use-case-1-n-linked-glycan-bvq5n5y6", "type": [ "Training material" ], "note": "Supporting protocol for use-case 1: N-linked glycan m/z candidate detection in \"M2aia - Interactive, fast and memory efficient analysis of 2D and 3D multi-modal mass spectrometry imaging data\"" }, { "url": "https://doi.org/10.24433/CO.2384502.v1", "type": [ "Training material" ], "note": "Supporting capsule for use-case 1: R-based processing in \"M²aia - Interactive, fast and memory efficient analysis of 2D and 3D multi-modal mass spectrometry imaging data\"" }, { "url": "https://doi.org/10.24433/CO.7662658.v1", "type": [ "Training material" ], "note": "Supporting capsule for use-case 1: Command-line application based pre-processing in \"M²aia - Interactive, fast and memory efficient analysis of 2D and 3D multi-modal mass spectrometry imaging data\"" } ], "publication": [], "credit": [], "community": null, "owner": "jtfc", "additionDate": "2021-06-22T12:35:44Z", "lastUpdate": "2024-02-26T14:30:06.751229Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Bowtie 2", "description": "Bowtie 2 is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly good at aligning reads of about 50 up to 100s or 1,000s of characters, and particularly good at aligning to relatively long (e.g. mammalian) genomes. Bowtie 2 indexes the genome with an FM Index to keep its memory footprint small: for the human genome, its memory footprint is typically around 3.2 GB. Bowtie 2 supports gapped, local, and paired-end alignment modes.", "homepage": "http://bowtie-bio.sourceforge.net/bowtie2/index.shtml", "biotoolsID": "bowtie2", "biotoolsCURIE": "biotools:bowtie2", "version": [], "otherID": [ { "value": "RRID:SCR_016368", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3198", "term": "Read mapping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Sequence alignment (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" }, { "uri": "http://edamontology.org/format_2573", "term": "SAM" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0102", "term": "Mapping" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_0102", "term": "Mapping" } ], "operatingSystem": [ "Linux" ], "language": [ "C++" ], "license": "GPL-3.0", "collectionID": [ "galaxyPasteur" ], "maturity": "Mature", "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/fmareuil/bowtie2/bowtie2/2.2.6.2", "type": [ "Galaxy service" ], "note": null } ], "download": [ { "url": "https://gitlab.com/sibyllewohlgemuth/cwl_files/raw/master/bowtie2.cwl", "type": "Tool wrapper (CWL)", "note": null, "version": null }, { "url": "https://gitlab.com/sibyllewohlgemuth/cwl_files/raw/master/bowtie2_build.cwl", "type": "Tool wrapper (CWL)", "note": null, "version": null }, { "url": "https://docker-ui.genouest.org/app/#/container/bioconda/bowtie2", "type": "Container file", "note": null, "version": null }, { "url": "https://anaconda.org/bioconda/bowtie2", "type": "Container file", "note": null, "version": null }, { "url": "https://tracker.debian.org/pkg/bowtie2", "type": "Software package", "note": "Link to the Debian package information. This form of the link is recommended by the Debian devs & Med team, and in the future all this information, including versions, will be pushed to GitHub automatically (matuskalas)", "version": "2.2.4-1, 2.3.0-2, 2.3.4.3-1, 2.3.5.1-1, 2.3.5.1-1" }, { "url": "https://bioconda.github.io/recipes/bowtie2/README.html", "type": "Software package", "note": "Link to the Bioconda package information. This form of the link is recommended by the Bioconda team, and in the future all this information, including versions (limit 100 chars), will be pushed to GitHub automatically (matuskalas)", "version": "2.3.5-0, 2.3.4.3-1 - 2.3.0-0, 2.2.8-2 - 2.2.1-0" } ], "documentation": [ { "url": "http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml", "type": [ "User manual" ], "note": null }, { "url": "https://github.com/BenLangmead/bowtie2", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/nmeth.1923", "pmid": "22388286", "pmcid": "PMC3322381", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Fast gapped-read alignment with Bowtie 2", "abstract": "As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy. © 2012 Nature America, Inc. All rights reserved.", "date": "2012-04-01T00:00:00Z", "citationCount": 18223, "authors": [ { "name": "Langmead B." }, { "name": "Salzberg S.L." } ], "journal": "Nature Methods" } }, { "doi": "10.1186/1471-2105-14-184", "pmid": "23758764", "pmcid": "PMC3694458", "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "Benchmarking short sequence mapping tools", "abstract": "Background: The development of next-generation sequencing instruments has led to the generation of millions of short sequences in a single run. The process of aligning these reads to a reference genome is time consuming and demands the development of fast and accurate alignment tools. However, the current proposed tools make different compromises between the accuracy and the speed of mapping. Moreover, many important aspects are overlooked while comparing the performance of a newly developed tool to the state of the art. Therefore, there is a need for an objective evaluation method that covers all the aspects. In this work, we introduce a benchmarking suite to extensively analyze sequencing tools with respect to various aspects and provide an objective comparison.Results: We applied our benchmarking tests on 9 well known mapping tools, namely, Bowtie, Bowtie2, BWA, SOAP2, MAQ, RMAP, GSNAP, Novoalign, and mrsFAST (mrFAST) using synthetic data and real RNA-Seq data. MAQ and RMAP are based on building hash tables for the reads, whereas the remaining tools are based on indexing the reference genome. The benchmarking tests reveal the strengths and weaknesses of each tool. The results show that no single tool outperforms all others in all metrics. However, Bowtie maintained the best throughput for most of the tests while BWA performed better for longer read lengths. The benchmarking tests are not restricted to the mentioned tools and can be further applied to others.Conclusion: The mapping process is still a hard problem that is affected by many factors. In this work, we provided a benchmarking suite that reveals and evaluates the different factors affecting the mapping process. Still, there is no tool that outperforms all of the others in all the tests. Therefore, the end user should clearly specify his needs in order to choose the tool that provides the best results. © 2013 Hatem et al.; licensee BioMed Central Ltd.", "date": "2013-06-07T00:00:00Z", "citationCount": 121, "authors": [ { "name": "Hatem A." }, { "name": "Bozdag D." }, { "name": "Toland A.E." }, { "name": "Catalyurek U.V." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1016/j.ygeno.2017.03.001", "pmid": "28286147", "pmcid": null, "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "Evaluation and assessment of read-mapping by multiple next-generation sequencing aligners based on genome-wide characteristics", "abstract": "© 2017 Elsevier Inc.Massive data produced due to the advent of next-generation sequencing (NGS) technology is widely used for biological researches and medical diagnosis. The crucial step in NGS analysis is read alignment or mapping which is computationally intensive and complex. The mapping bias tends to affect the downstream analysis, including detection of polymorphisms. In order to provide guidelines to the biologist for suitable selection of aligners; we have evaluated and benchmarked 5 different aligners (BWA, Bowtie2, NovoAlign, Smalt and Stampy) and their mapping bias based on characteristics of 5 microbial genomes. Two million simulated read pairs of various sizes (36 bp, 50 bp, 72 bp, 100 bp, 125 bp, 150 bp, 200 bp, 250 bp and 300 bp) were aligned. Specific alignment features such as sensitivity of mapping, percentage of properly paired reads, alignment time and effect of tandem repeats on incorrectly mapped reads were evaluated. BWA showed faster alignment followed by Bowtie2 and Smalt. NovoAlign and Stampy were comparatively slower. Most of the aligners showed high sensitivity towards long reads (> 100 bp) mapping. On the other hand NovoAlign showed higher sensitivity towards both short reads (36 bp, 50 bp, 72 bp) and long reads (> 100 bp) mappings; It also showed higher sensitivity towards mapping a complex genome like Plasmodium falciparum. The percentage of properly paired reads aligned by NovoAlign, BWA and Stampy were markedly higher. None of the aligners outperforms the others in the benchmark, however the aligners perform differently with genome characteristics. We expect that the results from this study will be useful for the end user to choose aligner, thus enhance the accuracy of read mapping.", "date": "2017-07-01T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Thankaswamy-Kosalai S." }, { "name": "Sen P." }, { "name": "Nookaew I." } ], "journal": "Genomics" } }, { "doi": "10.1186/1471-2164-15-264", "pmid": "24708189", "pmcid": "PMC4051166", "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "Comparison of mapping algorithms used in high-throughput sequencing: Application to Ion Torrent data", "abstract": "Background: The rapid evolution in high-throughput sequencing (HTS) technologies has opened up new perspectives in several research fields and led to the production of large volumes of sequence data. A fundamental step in HTS data analysis is the mapping of reads onto reference sequences. Choosing a suitable mapper for a given technology and a given application is a subtle task because of the difficulty of evaluating mapping algorithms.Results: In this paper, we present a benchmark procedure to compare mapping algorithms used in HTS using both real and simulated datasets and considering four evaluation criteria: computational resource and time requirements, robustness of mapping, ability to report positions for reads in repetitive regions, and ability to retrieve true genetic variation positions. To measure robustness, we introduced a new definition for a correctly mapped read taking into account not only the expected start position of the read but also the end position and the number of indels and substitutions. We developed CuReSim, a new read simulator, that is able to generate customized benchmark data for any kind of HTS technology by adjusting parameters to the error types. CuReSim and CuReSimEval, a tool to evaluate the mapping quality of the CuReSim simulated reads, are freely available. We applied our benchmark procedure to evaluate 14 mappers in the context of whole genome sequencing of small genomes with Ion Torrent data for which such a comparison has not yet been established.Conclusions: A benchmark procedure to compare HTS data mappers is introduced with a new definition for the mapping correctness as well as tools to generate simulated reads and evaluate mapping quality. The application of this procedure to Ion Torrent data from the whole genome sequencing of small genomes has allowed us to validate our benchmark procedure and demonstrate that it is helpful for selecting a mapper based on the intended application, questions to be addressed, and the technology used. This benchmark procedure can be used to evaluate existing or in-development mappers as well as to optimize parameters of a chosen mapper for any application and any sequencing platform. © 2014 Caboche et al.; licensee BioMed Central Ltd.", "date": "2014-04-05T00:00:00Z", "citationCount": 55, "authors": [ { "name": "Caboche S." }, { "name": "Audebert C." }, { "name": "Lemoine Y." }, { "name": "Hot D." } ], "journal": "BMC Genomics" } }, { "doi": "10.1093/bioinformatics/btu146", "pmid": "24626854", "pmcid": null, "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "Lacking alignments? The next-generation sequencing mapper segemehl revisited", "abstract": "Motivation: Next-generation sequencing has become an important tool in molecular biology. Various protocols to investigate genomic, transcriptomic and epigenomic features across virtually all species and tissues have been devised. For most of these experiments, one of the first crucial steps of bioinformatic analysis is the mapping of reads to reference genomes. Results: Here, we present thorough benchmarks of our read aligner segemehl in comparison with other state-of-the-art methods. Furthermore, we introduce the tool lack to rescue unmapped RNA-seq reads which works in conjunction with segemehl and many other frequently used split-read aligners. © The Author 2014.", "date": "2014-07-01T00:00:00Z", "citationCount": 46, "authors": [ { "name": "Otto C." }, { "name": "Stadler P.F." }, { "name": "Hoffmann S." } ], "journal": "Bioinformatics" } }, { "doi": "10.7490/f1000research.1114334.1", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Institut Français de Bioinformatique", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Ben Langmead", "email": null, "url": "http://bowtie-bio.sourceforge.net/bowtie2/index.shtml", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null }, { "name": "Ben Langmead", "email": null, "url": "http://bowtie-bio.sourceforge.net/bowtie2/index.shtml", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "swohlgemuth", "additionDate": "2016-03-24T16:39:49Z", "lastUpdate": "2024-02-16T10:45:32.677126Z", "editPermission": { "type": "group", "authors": [ "swohlgemuth", "rioualen" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "The Human Protein Atlas", "description": "Database with millions of high-resolution images. Expression and localization of proteins in a large variety of normal human tissues, cancer cells and cell lines with the aid of immunohistochemistry (IHC) images and immunofluorescence (IF) confocal microscopy images.", "homepage": "http://www.proteinatlas.org/", "biotoolsID": "proteinatlas", "biotoolsCURIE": "biotools:proteinatlas", "version": [], "otherID": [ { "value": "RRID:SCR_006710", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0968", "term": "Keyword" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Gene expression data" }, "format": [] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1033", "term": "Ensembl gene ID" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0916", "term": "Gene report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1026", "term": "Gene symbol" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0916", "term": "Gene report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2772", "term": "HPA antibody id" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0916", "term": "Gene report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_0623", "term": "Gene and protein families" }, { "uri": "http://edamontology.org/topic_2640", "term": "Oncology" }, { "uri": "http://edamontology.org/topic_1317", "term": "Structural biology" }, { "uri": "http://edamontology.org/topic_0140", "term": "Protein targeting and localisation" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_2815", "term": "Humans" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "gpcr" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [ "Data" ], "elixirNode": [ "Sweden" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://www.proteinatlas.org/about", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1126/science.1260419", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Tissue-based map of the human proteome", "abstract": "Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes.We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.", "date": "2015-01-23T00:00:00Z", "citationCount": 8758, "authors": [ { "name": "Uhlen M." }, { "name": "Fagerberg L." }, { "name": "Hallstrom B.M." }, { "name": "Lindskog C." }, { "name": "Oksvold P." }, { "name": "Mardinoglu A." }, { "name": "Sivertsson A." }, { "name": "Kampf C." }, { "name": "Sjostedt E." }, { "name": "Asplund A." }, { "name": "Olsson I." }, { "name": "Edlund K." }, { "name": "Lundberg E." }, { "name": "Navani S." }, { "name": "Szigyarto C.A.-K." }, { "name": "Odeberg J." }, { "name": "Djureinovic D." }, { "name": "Takanen J.O." }, { "name": "Hober S." }, { "name": "Alm T." }, { "name": "Edqvist P.-H." }, { "name": "Berling H." }, { "name": "Tegel H." }, { "name": "Mulder J." }, { "name": "Rockberg J." }, { "name": "Nilsson P." }, { "name": "Schwenk J.M." }, { "name": "Hamsten M." }, { "name": "Von Feilitzen K." }, { "name": "Forsberg M." }, { "name": "Persson L." }, { "name": "Johansson F." }, { "name": "Zwahlen M." }, { "name": "Von Heijne G." }, { "name": "Nielsen J." }, { "name": "Ponten F." } ], "journal": "Science" } } ], "credit": [ { "name": "bils.se", "email": null, "url": "https://bils.se/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Support", "email": "contact@proteinatlas.org", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "mikael.borg@bils.se", "additionDate": "2015-12-06T15:18:35Z", "lastUpdate": "2024-02-15T12:40:29.455013Z", "editPermission": { "type": "group", "authors": [ "mbermudez1" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ClinVar", "description": "A freely accessible, public archive of reports of relationships among medically important variants and phenotypes hosted by the NCBI. It integrates and cross-references data from multiple databases at NCBI. In addition to dbSNP and dbVar, it depends on MedGen to represent phenotype, Gene to represent genes, and on human RefSeqs to represent the location of sequence variation. Each record represents the submitter, the variation and the phenotype.", "homepage": "http://www.ncbi.nlm.nih.gov/clinvar/", "biotoolsID": "clinvar", "biotoolsCURIE": "biotools:clinvar", "version": [], "otherID": [ { "value": "RRID:SCR_006169", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Deposition" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_3197", "term": "Genetic variation analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_2815", "term": "Human biology" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "RD-connect", "Rare Disease" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://www.ncbi.nlm.nih.gov/clinvar/intro/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkt1113", "pmid": "24234437", "pmcid": "PMC3965032", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "ClinVar: Public archive of relationships among sequence variation and human phenotype", "abstract": "ClinVar (http://www.ncbi.nlm.nih.gov/clinvar/) provides a freely available archive of reports of relationships among medically important variants and phenotypes. ClinVar accessions submissions reporting human variation, interpretations of the relationship of that variation to human health and the evidence supporting each interpretation. The database is tightly coupled with dbSNP and dbVar, which maintain information about the location of variation on human assemblies. ClinVar is also based on the phenotypic descriptions maintained in MedGen (http://www.ncbi.nlm.nih.gov/medgen). Each ClinVar record represents the submitter, the variation and the phenotype, i.e. the unit that is assigned an accession of the format SCV000000000.0. The submitter can update the submission at any time, in which case a new version is assigned. To facilitate evaluation of the medical importance of each variant, ClinVar aggregates submissions with the same variation/phenotype combination, adds value from other NCBI databases, assigns a distinct accession of the format RCV000000000.0 and reports if there are conflicting clinical interpretations. Data in ClinVar are available in multiple formats, including html, download as XML, VCF or tab-delimited subsets. Data from ClinVar are provided as annotation tracks on genomic RefSeqs and are used in tools such as Variation Reporter (http://www.ncbi.nlm.nih.gov/variation/tools/reporter), which reports what is known about variation based on user-supplied locations. © 2013 The Author(s). Published by Oxford University Press.", "date": "2014-01-01T00:00:00Z", "citationCount": 1487, "authors": [ { "name": "Landrum M.J." }, { "name": "Lee J.M." }, { "name": "Riley G.R." }, { "name": "Jang W." }, { "name": "Rubinstein W.S." }, { "name": "Church D.M." }, { "name": "Maglott D.R." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkx1153", "pmid": "29165669", "pmcid": "PMC5753237", "type": [], "version": null, "note": null, "metadata": { "title": "ClinVar: Improving access to variant interpretations and supporting evidence", "abstract": "© Published by Oxford University Press on behalf of Nucleic Acids Research 2017.ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease, maintained at the National Institutes of Health. Interpretations of the clinical significance of variants are submitted by clinical testing laboratories, research laboratories, expert panels and other groups. ClinVar aggregates data by variant-disease pairs, and by variant (or set of variants). Data aggregated by variant are accessible on the website, in an improved set of variant call format files and as a new comprehensive XML report. ClinVar recently started accepting submissions that are focused primarily on providing phenotypic information for individuals who have had genetic testing. Submissions may come from clinical providers providing their own interpretation of the variant ('provider interpretation') or from groups such as patient registries that primarily provide phenotypic information from patients ('phenotyping only'). ClinVar continues to make improvements to its search and retrieval functions. Several new fields are now indexed for more precise searching, and filters allow the user to narrow down a large set of search results.", "date": "2018-01-01T00:00:00Z", "citationCount": 1190, "authors": [ { "name": "Landrum M.J." }, { "name": "Lee J.M." }, { "name": "Benson M." }, { "name": "Brown G.R." }, { "name": "Chao C." }, { "name": "Chitipiralla S." }, { "name": "Gu B." }, { "name": "Hart J." }, { "name": "Hoffman D." }, { "name": "Jang W." }, { "name": "Karapetyan K." }, { "name": "Katz K." }, { "name": "Liu C." }, { "name": "Maddipatla Z." }, { "name": "Malheiro A." }, { "name": "McDaniel K." }, { "name": "Ovetsky M." }, { "name": "Riley G." }, { "name": "Zhou G." }, { "name": "Holmes J.B." }, { "name": "Kattman B.L." }, { "name": "Maglott D.R." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Donna R. Maglott", "email": "maglott@ncbi.nlm.nih.gov", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "ELIXIR-EE", "additionDate": "2017-03-04T22:39:18Z", "lastUpdate": "2024-02-14T13:12:50.053374Z", "editPermission": { "type": "group", "authors": [ "sergitobara", "Friederike" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "HGMD", "description": "The Human Gene Mutation Database (HGMD) - comprehensive collection of germline mutations in nuclear genes that underlie, or are associated with, human inherited disease. It is a flexible resource that can be adapted to a broad range of applications including searching for an overview of known mutations associated with a particular disease, interpreting clinical test results or looking for the likely causal mutation in a list of variants.", "homepage": "http://www.hgmd.org", "biotoolsID": "hgmd", "biotoolsCURIE": "biotools:hgmd", "version": [], "otherID": [ { "value": "RRID:SCR_001621", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3224", "term": "Gene set testing" }, { "uri": "http://edamontology.org/operation_3196", "term": "Genotyping" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_3197", "term": "Genetic variation analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_2815", "term": "Human biology" }, { "uri": "http://edamontology.org/topic_0634", "term": "Pathology" }, { "uri": "http://edamontology.org/topic_3366", "term": "Data integration and warehousing" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "RD-connect", "Rare Disease" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Restricted access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://www.hgmd.cf.ac.uk/docs/new_help.html", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1007/s00439-013-1358-4", "pmid": "24077912", "pmcid": "PMC3898141", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The Human Gene Mutation Database: Building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine", "abstract": "The Human Gene Mutation Database (HGMD®) is a comprehensive collection of germline mutations in nuclear genes that underlie, or are associated with, human inherited disease. By June 2013, the database contained over 141,000 different lesions detected in over 5,700 different genes, with new mutation entries currently accumulating at a rate exceeding 10,000 per annum. HGMD was originally established in 1996 for the scientific study of mutational mechanisms in human genes. However, it has since acquired a much broader utility as a central unified disease-oriented mutation repository utilized by human molecular geneticists, genome scientists, molecular biologists, clinicians and genetic counsellors as well as by those specializing in biopharmaceuticals, bioinformatics and personalized genomics. The public version of HGMD (http://www.hgmd.org) is freely available to registered users from academic institutions/non-profit organizations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via BIOBASE GmbH. © 2013 The Author(s).", "date": "2014-01-01T00:00:00Z", "citationCount": 904, "authors": [ { "name": "Stenson P.D." }, { "name": "Mort M." }, { "name": "Ball E.V." }, { "name": "Shaw K." }, { "name": "Phillips A.D." }, { "name": "Cooper D.N." } ], "journal": "Human Genetics" } }, { "doi": "10.1136/jmg.2007.055210", "pmid": "18245393", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Human Gene Mutation Database: Towards a comprehensive central mutation database", "abstract": "", "date": "2008-02-01T00:00:00Z", "citationCount": 87, "authors": [ { "name": "Stenson P.D." }, { "name": "Ball E." }, { "name": "Howells K." }, { "name": "Phillips A." }, { "name": "Mort M." }, { "name": "Cooper D.N." } ], "journal": "Journal of Medical Genetics" } }, { "doi": "10.1002/humu.10212", "pmid": "12754702", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Human Gene Mutation Database (HGMD®): 2003 Update", "abstract": "The Human Gene Mutation Database (HGMD) constitutes a comprehensive core collection of data on germ-line mutations in nuclear genes underlying or associated with human inherited disease (www.hgmd.org). Data catalogued includes: single base-pair substitutions in coding, regulatory and splicing-relevant regions; micro-deletions and micro-insertions; indels; triplet repeat expansions as well as gross deletions; insertions; duplications; and complex rearrangements. Each mutation is entered into HGMD only once in order to avoid confusion between recurrent and identical-by-descent lesions. By March 2003, the database contained in excess of 39,415 different lesions detected in 1,516 different nuclear genes, with new entries currently accumulating at a rate exceeding 5,000 per annum. Since its inception, HGMD has been expanded to include cDNA reference sequences for more than 87% of listed genes, splice junction sequences, disease-associated and functional polymorphisms, as well as links to data present in publicly available online locus-specific mutation databases. Although HGMD has recently entered into a licensing agreement with Celera Genomics (Rockville, MD), mutation data will continue to be made freely available via the Internet. © 2003 Wiley-Liss, Inc.", "date": "2003-06-16T00:00:00Z", "citationCount": 1269, "authors": [ { "name": "Stenson P.D." }, { "name": "Ball E.V." }, { "name": "Mort M." }, { "name": "Phillips A.D." }, { "name": "Shiel J.A." }, { "name": "Thomas N.S.T." }, { "name": "Abeysinghe S." }, { "name": "Krawczak M." }, { "name": "Cooper D.N." } ], "journal": "Human Mutation" } }, { "doi": "10.1186/gm13", "pmid": "19348700", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "The human gene mutation database: 2008 update", "abstract": "The Human Gene Mutation Database (HGMD®) is a comprehensive core collection of germlinemutations in nuclear genes that underlie or are associated with human inherited disease. Here we summarize the history of the database and its current resources. By December 2008, thedatabase contained over 85,000 different lesions detected in 3,253 ifferent genes, with new entries currently accumulating at a rate exceeding 9,000 per annum. Although originally established for the scientific study of mutational mechanisms in human genes, HGMD has since acquired a much broader utility for researchers, physicians, clinicians and genetic counselors as well as for companies specializing in biopharmaceuticals, bioinformatics and personalized genomics. HGMD was first made publicly available in April 1996, and a collaboration was initiated in 2006 between HGMD and BIOBASE GmbH. This cooperative agreement covers the exclusive worldwide marketing of the most up-to-date (subscription) version of HGMD, HGMD Professional, to academic, clinical and commercial users. © 2009 BioMed Central Ltd.", "date": "2009-01-22T00:00:00Z", "citationCount": 665, "authors": [ { "name": "Stenson P.D." }, { "name": "Mort M." }, { "name": "Ball E.V." }, { "name": "Howells K." }, { "name": "Phillips P.D." }, { "name": "Cooper D.N." }, { "name": "Thomas N.S.T." } ], "journal": "Genome Medicine" } }, { "doi": "10.1007/s00439-017-1779-6", "pmid": "28349240", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies", "abstract": "© 2017, The Author(s).The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that underlie, or are closely associated with human inherited disease. At the time of writing (March 2017), the database contained in excess of 203,000 different gene lesions identified in over 8000 genes manually curated from over 2600 journals. With new mutation entries currently accumulating at a rate exceeding 17,000 per annum, HGMD represents de facto the central unified gene/disease-oriented repository of heritable mutations causing human genetic disease used worldwide by researchers, clinicians, diagnostic laboratories and genetic counsellors, and is an essential tool for the annotation of next-generation sequencing data. The public version of HGMD (http://www.hgmd.org) is freely available to registered users from academic institutions and non-profit organisations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via QIAGEN Inc.", "date": "2017-06-01T00:00:00Z", "citationCount": 724, "authors": [ { "name": "Stenson P.D." }, { "name": "Mort M." }, { "name": "Ball E.V." }, { "name": "Evans K." }, { "name": "Hayden M." }, { "name": "Heywood S." }, { "name": "Hussain M." }, { "name": "Phillips A.D." }, { "name": "Cooper D.N." } ], "journal": "Human Genetics" } } ], "credit": [ { "name": "Contact Form", "email": null, "url": "http://www.hgmd.cf.ac.uk/docs/comment_form.html", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "ELIXIR-EE", "additionDate": "2017-03-04T22:58:49Z", "lastUpdate": 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{ "data": { "uri": "http://edamontology.org/data_2531", "term": "Experiment report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2374", "term": "Spot serial number" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2531", "term": "Experiment report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "Proteomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://world-2dpage.expasy.org/swiss-2dpage/docs/manch2d.html", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1002/pmic.200300830", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "SWISS-2DPAGE, ten years later", "abstract": "The SWISS-2DPAGE database was established in 1993 and is maintained collaboratively by the Swiss Institute of Bioinformatics (SIB) and the Biomedical Proteomics Research Group (BPRG) of the Geneva University Hospital. During these years, SWISS-2DPAGE underwent constant modification and improvement. Current content includes about 4000 identified spots corresponding to 1200 different protein entries in 36 reference maps from human, mouse, Arabidopsis thaliana, Dictyostelium discoideum, Escherichia coli, Saccharomyces cerevisiae and Staphylococcus aureus origins. With a high level of annotation and integration with other relevant databases, SWISS-2DPAGE is a reference source in the proteomics world. Queries to SWISS-2DPAGE database currently reach 1000 hits per day.", "date": "2004-08-01T00:00:00Z", "citationCount": 88, "authors": [ { "name": "Hoogland C." }, { "name": "Mostaguir K." }, { "name": "Sanchez J.-C." }, { "name": "Hochstrasser D.F." }, { "name": "Appel R.D." } ], "journal": "Proteomics" } } ], "credit": [ { "name": "SIB Swiss Institute of Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Contributor" ], "note": null }, { "name": null, "email": null, "url": "http://world-2dpage.expasy.org/contact", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "SIB", "additionDate": "2015-10-09T16:38:04Z", "lastUpdate": "2024-02-14T13:12:44.876955Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "Friederike" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "REDItools", "description": "Python scripts to detect RNA editing in deep transcriptome sequencing data (RNAseq)", "homepage": "https://github.com/BioinfoUNIBA/REDItools", "biotoolsID": "reditools", "biotoolsCURIE": "biotools:reditools", "version": [ "1.3", "2.0" ], "otherID": [ { "value": "RRID:SCR_012133", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2945", "term": "Analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1916", "term": "Alignment" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2526", "term": "Text data" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "Run REDItools on RNA sequences", "cmd": "REDItoolDnaRna.py -i rnaseq.bam -f myreference.fa -o myoutputfolder" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Python" ], "license": "MIT", "collectionID": [ "ELIXIR-ITA-CNR" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/BioinfoUNIBA/REDItools", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btt287", "pmid": "23742983", "pmcid": null, "type": [ "Primary" ], "version": "1.0-1.3", "note": null, "metadata": { "title": "REDItools: High-throughput RNA editing detection made easy", "abstract": "The reliable detection of RNA editing sites from massive sequencing data remains challenging and, although several methodologies have been proposed, no computational tools have been released to date. Here, we introduce REDItools a suite of python scripts to perform high-throughput investigation of RNA editing using next-generation sequencing data.Availability and implementation: REDItools are in python programming language and freely available at http://code.google. com/p/reditools/.Contact: or graziano.pesole@uniba.itSupplementary information: Supplementary data are available at Bioinformatics online. © 2013 The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.", "date": "2013-07-15T00:00:00Z", "citationCount": 201, "authors": [ { "name": "Picardi E." }, { "name": "Pesole G." } ], "journal": "Bioinformatics" } }, { "doi": "10.1186/s12859-020-03562-x", "pmid": "32838738", "pmcid": "PMC7446188", "type": [], "version": "2.0", "note": null, "metadata": { "title": "HPC-REDItools: A novel HPC-aware tool for improved large scale RNA-editing analysis", "abstract": "Background: RNA editing is a widespread co-/post-transcriptional mechanism that alters primary RNA sequences through the modification of specific nucleotides and it can increase both the transcriptome and proteome diversity. The automatic detection of RNA-editing from RNA-seq data is computational intensive and limited to small data sets, thus preventing a reliable genome-wide characterisation of such process. Results: In this work we introduce HPC-REDItools, an upgraded tool for accurate RNA-editing events discovery from large dataset repositories. Availability: https://github.com/BioinfoUNIBA/REDItools2. Conclusions: HPC-REDItools is dramatically faster than the previous version, REDItools, enabling big-data analysis by means of a MPI-based implementation and scaling almost linearly with the number of available cores.", "date": "2020-08-21T00:00:00Z", "citationCount": 21, "authors": [ { "name": "Flati T." }, { "name": "Gioiosa S." }, { "name": "Spallanzani N." }, { "name": "Tagliaferri I." }, { "name": "Diroma M.A." }, { "name": "Pesole G." }, { "name": "Chillemi G." }, { "name": "Picardi E." }, { "name": "Castrignano T." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1038/s41596-019-0279-7", "pmid": "31996844", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Investigating RNA editing in deep transcriptome datasets with REDItools and REDIportal", "abstract": "RNA editing is a widespread post-transcriptional mechanism able to modify transcripts through insertions/deletions or base substitutions. It is prominent in mammals, in which millions of adenosines are deaminated to inosines by members of the ADAR family of enzymes. A-to-I RNA editing has a plethora of biological functions, but its detection in large-scale transcriptome datasets is still an unsolved computational task. To this aim, we developed REDItools, the first software package devoted to the RNA editing profiling in RNA-sequencing (RNAseq) data. It has been successfully used in human transcriptomes, proving the tissue and cell type specificity of RNA editing as well as its pervasive nature. Outcomes from large-scale REDItools analyses on human RNAseq data have been collected in our specialized REDIportal database, containing more than 4.5 million events. Here we describe in detail two bioinformatic procedures based on our computational resources, REDItools and REDIportal. In the first procedure, we outline a workflow to detect RNA editing in the human cell line NA12878, for which transcriptome and whole genome data are available. In the second procedure, we show how to identify dysregulated editing at specific recoding sites in post-mortem brain samples of Huntington disease donors. On a 64-bit computer running Linux with ≥32 GB of random-access memory (RAM), both procedures should take ~76 h, using 4 to 24 cores. Our protocols have been designed to investigate RNA editing in different organisms with available transcriptomic and/or genomic reads. Scripts to complete both procedures and a docker image are available at https://github.com/BioinfoUNIBA/REDItools.", "date": "2020-03-01T00:00:00Z", "citationCount": 69, "authors": [ { "name": "Lo Giudice C." }, { "name": "Tangaro M.A." }, { "name": "Pesole G." }, { "name": "Picardi E." } ], "journal": "Nature Protocols" } }, { "doi": "10.1007/978-1-0716-1307-8_14", "pmid": "33835447", "pmcid": null, "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "RNA Editing Detection in HPC Infrastructures", "abstract": "RNA editing by A-to-I deamination is a relevant co/posttranscriptional modification carried out by ADAR enzymes. In humans, it has pivotal cellular effects and its deregulation has been linked to a variety of human disorders including neurological and neurodegenerative diseases and cancer. Despite its biological relevance, the detection of RNA editing variants in large transcriptome sequencing experiments (RNAseq) is yet a challenging computational task. To drastically reduce computing times we have developed a novel REDItools version able to identify A-to-I events in huge amount of RNAseq data employing High Performance Computing (HPC) infrastructures. Here we show how to use REDItools v2 in HPC systems.", "date": "2021-01-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Giudice C.L." }, { "name": "Mansi L." }, { "name": "Flati T." }, { "name": "Gioiosa S." }, { "name": "Chillemi G." }, { "name": "Libro P." }, { "name": "Castrignano T." }, { "name": "Pesole G." }, { "name": "Picardi E." } ], "journal": "Methods in Molecular Biology" } }, { "doi": "10.1002/0471250953.bi1212s49", "pmid": "25754992", "pmcid": null, "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "Using REDItools to detect RNA editing events in NGS datasets", "abstract": "RNAediting is a post-transcriptional/co-transcriptional molecular phenomenon whereby a genetic message is modified from the corresponding DNA template by means of substitutions, insertions, and/or deletions. It occurs in a variety of organisms and different cellular locations through evolutionally and biochemically unrelated proteins. RNA editing has a plethora of biological effects including the modulation of alternative splicing and fine-tuning of gene expression. RNA editing events by base substitutions can be detected on a genomic scale by NGS technologies through the REDItools package, an ad hoc suite of Python scripts to study RNA editing using RNA-Seq and DNA-Seq data or RNA-Seq data alone. REDItools implement effective filters to minimize biases due to sequencing errors, mapping errors, and SNPs. The package is freely available at Google Code repository (http://code.google.com/p/reditools/) and released under the MIT license. In the present unit we show three basic protocols corresponding to three main REDItools scripts.", "date": "2015-01-01T00:00:00Z", "citationCount": 25, "authors": [ { "name": "Picardi E." }, { "name": "D'Erchia A.M." }, { "name": "A. Antonio" }, { "name": "G. Graziano" } ], "journal": "Current Protocols in Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-CNR", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-6549-0114", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Ernesto Picardi", "email": "ernesto.picardi@uniba.it", "url": "https://www.uniba.it/docenti/picardi-ernesto/en", "orcidid": "https://orcid.org/0000-0002-6549-0114", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "ELIXIR-ITA-CNR", "additionDate": "2015-02-05T13:24:16Z", "lastUpdate": "2024-02-09T14:59:52.330758Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-ITA-BARI" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MUSCLE (EBI)", "description": "Sequence alignment using the Multiple Sequence Comparison by Log-Expectation (MUSCLE) method", "homepage": "https://www.ebi.ac.uk/jdispatcher/msa/muscle", "biotoolsID": "muscle_ebi", "biotoolsCURIE": "biotools:muscle_ebi", "version": [ "1" ], "otherID": [ { "value": "RRID:SCR_011812", "type": "rrid", "version": null } ], "relation": [ { "biotoolsID": "muscle", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0492", "term": "Multiple sequence alignment" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0863", "term": "Sequence alignment" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "MUSCLE", "EBI Tools", "Job Dispatcher Tools" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.ebi.ac.uk/about/contact/support/job-dispatcher-services", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://www.drive5.com/muscle/", "type": "Downloads page", "note": null, "version": null } ], "documentation": [ { "url": "http://www.ebi.ac.uk/about/terms-of-use", "type": [ "Terms of use" ], "note": null }, { "url": "https://www.ebi.ac.uk/jdispatcher/help", "type": [ "General" ], "note": null }, { "url": "https://www.drive5.com/muscle/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkh340", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "MUSCLE: Multiple sequence alignment with high accuracy and high throughput", "abstract": "We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5.com/muscle. © Oxford University Press 20004; all rights reserved.", "date": "2004-07-09T00:00:00Z", "citationCount": 32864, "authors": [ { "name": "Edgar R.C." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkac240", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Search and sequence analysis tools services from EMBL-EBI in 2022", "abstract": "The EMBL-EBI search and sequence analysis tools frameworks provide integrated access to EMBL-EBI's data resources and core bioinformatics analytical tools. EBI Search (https://www.ebi.ac.uk/ebisearch) provides a full-text search engine across nearly 5 billion entries, while the Job Dispatcher tools framework (https://www.ebi.ac.uk/services) enables the scientific community to perform a diverse range of sequence analysis using popular bioinformatics applications. Both allow users to interact through user-friendly web applications, as well as via RESTful and SOAP-based APIs. Here, we describe recent improvements to these services and updates made to accommodate the increasing data requirements during the COVID-19 pandemic.", "date": "2022-07-05T00:00:00Z", "citationCount": 696, "authors": [ { "name": "Madeira F." }, { "name": "Pearce M." }, { "name": "Tivey A.R.N." }, { "name": "Basutkar P." }, { "name": "Lee J." }, { "name": "Edbali O." }, { "name": "Madhusoodanan N." }, { "name": "Kolesnikov A." }, { "name": "Lopez R." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Robert Edgar", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "EMBL-EBI", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Job Dispatcher", "email": null, "url": "https://www.ebi.ac.uk/jdispatcher", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Project", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "jdispatcher", "additionDate": "2015-01-29T15:47:31Z", "lastUpdate": "2024-02-05T19:06:27.801304Z", "editPermission": { "type": "group", "authors": [ "biomadeira", "nandana" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "X-omics ACTION demonstrator multi-omics analysis workflow", "description": "This multi-omics data analysis workflow was developed as part of a case study investigating shared patterns between multi-omics data and childhood externalizing behaviour. The modular Nextflow workflow was implemented using FAIR practices. It comprises genome-wide DNA methylation, targeted metabolomics and behaviour data pre-processing, and integrative analysis methods. Individuals of a cohort are clustered using Similarity Network Fusion (SNF), latent feature dimensions are uncovered using different unsupervised methods including Multi-Omics Factor Analysis (MOFA) and Multiple Correspondence Analysis (MCA), and correlations between -omics and phenotype dimensions are determined in downstream analyses including results visualisation.", "homepage": "https://workflowhub.eu/workflows/402", "biotoolsID": "x-omics_action_demonstrator_multi-omics_analysis_workflow", "biotoolsCURIE": "biotools:x-omics_action_demonstrator_multi-omics_analysis_workflow", "version": [ "2.2", "2.3" ], "otherID": [ { "value": "RRID:SCR_024719", "type": "rrid", "version": null } ], "relation": [ { "biotoolsID": "nextflow", "type": "uses" } ], "function": [], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3391", "term": "Omics" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_3173", "term": "Epigenomics" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python", "R" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Xomics/ACTIONdemonstrator_workflow", "type": [ "Repository" ], "note": null }, { "url": "https://doi.org/10.48546/workflowhub.workflow.402.8", "type": [ "Software catalogue" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/Xomics/ACTIONdemonstrator_workflow/blob/main/Documentation.md", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/gigascience/giad115", "pmid": "38217405", "pmcid": "PMC10787363", "type": [ "Other" ], "version": null, "note": "Journal article (technical note)", "metadata": null } ], "credit": [], "community": null, "owner": "aniehues", "additionDate": "2023-11-23T10:53:51.802150Z", "lastUpdate": "2024-01-24T06:19:18.681462Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null } ] }