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GET /api/t/?operation=%22Sequence%20analysis%22
{ "count": 1114, "next": "?page=2", "previous": null, "list": [ { "name": "SILVAngs", "description": "SILVAngs is a data analysis service for ribosomal RNA gene (rDNA) amplicon reads from high-throughput sequencing (next-generation sequencing (NGS)) approaches based on an automatic software pipeline. It uses the SILVA rDNA databases, taxonomies, and alignments as a reference. It facilitates the classification of rDNA reads and provides a wealth of results (tables, graphs and sequence files) for download.", "homepage": "https://ngs.arb-silva.de", "biotoolsID": "silvangs", "biotoolsCURIE": "biotools:silvangs", "version": [ "1.9.10" ], "otherID": [], "relation": [ { "biotoolsID": "silva", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" }, { "uri": "http://edamontology.org/operation_2478", "term": "Nucleic acid sequence analysis" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" }, { "uri": "http://edamontology.org/operation_2428", "term": "Validation" }, { "uri": "http://edamontology.org/operation_0291", "term": "Sequence clustering" }, { "uri": "http://edamontology.org/operation_0292", "term": "Sequence alignment" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2082", "term": "Matrix" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_1246", "term": "Sequence cluster (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] }, { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] } ], "note": "The pipeline accepts input data in Multi-Fasta format with each input file representing one sample. Samples that belong to one project (a transect, timeseries etc.) should be uploaded as a single SILVAngs project.", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3050", "term": "Biodiversity" }, { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [ "de.NBI", "de.NBI-biodata", "DSMZ Digital Diversity" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": null, "elixirPlatform": [ "Data" ], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://www.arb-silva.de/fileadmin/silva_databases/sngs/SILVAngs_User_Guide.pdf", "type": [ "User manual" ], "note": null }, { "url": "https://www.arb-silva.de/documentation/silvangs/userfaq/", "type": [ "FAQ" ], "note": null }, { "url": "https://www.arb-silva.de/footer/sngs-termsofuse", "type": [ "Terms of use" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gks1219", "pmid": "23193283", "pmcid": "PMC3531112", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3194 778 small subunit and 288717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches. © The Author(s) 2012.", "date": "2013-01-01T00:00:00Z", "citationCount": 22633, "authors": [ { "name": "Quast C." }, { "name": "Pruesse E." }, { "name": "Yilmaz P." }, { "name": "Gerken J." }, { "name": "Schweer T." }, { "name": "Yarza P." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkt1209", "pmid": "24293649", "pmcid": "PMC3965112", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The SILVA and \"all-species Living Tree Project (LTP)\" taxonomic frameworks", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive resource for up-to-date quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. SILVA provides a manually curated taxonomy for all three domains of life, based on representative phylogenetic trees for the small- and large-subunit rRNA genes. This article describes the improvements the SILVA taxonomy has undergone in the last 3 years. Specifically we are focusing on the curation process, the various resources used for curation and the comparison of the SILVA taxonomy with Greengenes and RDP-II taxonomies. Our comparisons not only revealed a reasonable overlap between the taxa names, but also points to significant differences in both names and numbers of taxa between the three resources. © 2013 The Author(s). Published by Oxford University Press.", "date": "2014-01-01T00:00:00Z", "citationCount": 2590, "authors": [ { "name": "Yilmaz P." }, { "name": "Parfrey L.W." }, { "name": "Yarza P." }, { "name": "Gerken J." }, { "name": "Pruesse E." }, { "name": "Quast C." }, { "name": "Schweer T." }, { "name": "Peplies J." }, { "name": "Ludwig W." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/bts252", "pmid": "22556368", "pmcid": "PMC3389763", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes", "abstract": "Motivation: In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements.Results: In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. © The Author(s) 2012. Published by Oxford University Press.", "date": "2012-07-01T00:00:00Z", "citationCount": 2408, "authors": [ { "name": "Pruesse E." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "SILVA Team", "email": "ngs-contact@arb-silva.de", "url": "https://www.arb-silva.de/contact/team/", "orcidid": null, "gridid": "grid.507782.f", "rorid": "027z9pz32", "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures", "email": "hub@dsmz.de", "url": "https://www.dsmz.de", "orcidid": null, "gridid": "grid.420081.f", "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "silva", "additionDate": "2016-09-30T07:30:11Z", "lastUpdate": "2025-06-30T13:26:39.251875Z", "editPermission": { "type": "group", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "NanoPack", "description": "Visualizing and processing long-read sequencing data.", "homepage": "https://github.com/wdecoster/nanopack", "biotoolsID": "nanopack", "biotoolsCURIE": "biotools:nanopack", "version": [ "1.1.0" ], "otherID": [], "relation": [ { "biotoolsID": "nanoplot", "type": "includes" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2403", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/operation_0564", "term": "Sequence visualisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Python" ], "license": null, "collectionID": [ "VIB" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/wdecoster/nanopack", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/bty149", "pmid": "29547981", "pmcid": "PMC6061794", "type": [], "version": null, "note": null, "metadata": { "title": "NanoPack: Visualizing and processing long-read sequencing data", "abstract": "Summary: Here we describe NanoPack, a set of tools developed for visualization and processing of long-read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences. Availability and implementation: The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.", "date": "2018-08-01T00:00:00Z", "citationCount": 1840, "authors": [ { "name": "De Coster W." }, { "name": "D'Hert S." }, { "name": "Schultz D.T." }, { "name": "Cruts M." }, { "name": "Van Broeckhoven C." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Wouter De Coster", "email": "wouter.decoster@molgen.vib-ua.be", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "d.gabrielaitis", "additionDate": "2018-07-01T13:17:42Z", "lastUpdate": "2025-06-18T12:21:28.393467Z", "editPermission": { "type": "group", "authors": [ "bits@vib.be" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MuGVRE", "description": "The MuG Virtual Research Environment is an analysis platform for 3D/4D genomics analyses. It integrates genomics tools for chromatin dynamics data.", "homepage": "https://www.multiscalegenomics.eu/", "biotoolsID": "mugvre", "biotoolsCURIE": "biotools:mugvre", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "nucleosome_dynamics", "type": "includes" }, { "biotoolsID": "tadbit", "type": "includes" }, { "biotoolsID": "jbrowse", "type": "includes" }, { "biotoolsID": "ngl", "type": "includes" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0292", "term": "Sequence alignment" }, { "uri": "http://edamontology.org/operation_3198", "term": "Read mapping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_3210", "term": "Genome index" }, "format": [] } ], "output": [ { "data": { "uri": 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knowledge platform dedicated to human proteins. This resource contained a wealth of high-quality data on all the human proteins that are produced by the 20'000 protein-coding genes found in the human genome. 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DM us with feedback!" }, { "url": "https://www.expasy.org/resources/nextprot", "type": [ "Software catalogue" ], "note": "neXtProt entry in Expasy" } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkz995", "pmid": "31724716", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The neXtProt knowledgebase in 2020: Data, tools and usability improvements", "abstract": "The neXtProt knowledgebase (https://www.nextprot.org) is an integrative resource providing both data on human protein and the tools to explore these. In order to provide comprehensive and up-to-date data, we evaluate and add new data sets. We describe the incorporation of three new data sets that provide expression, function, protein-protein binary interaction, post-translational modifications (PTM) and variant information. New SPARQL query examples illustrating uses of the new data were added. neXtProt has continued to develop tools for proteomics. We have improved the peptide uniqueness checker and have implemented a new protein digestion tool. Together, these tools make it possible to determine which proteases can be used to identify trypsin-resistant proteins by mass spectrometry. In terms of usability, we have finished revamping our web interface and completely rewritten our API. Our SPARQL endpoint now supports federated queries. All the neXtProt data are available via our user interface, API, SPARQL endpoint and FTP site, including the new PEFF 1.0 format files. 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