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GET /api/t/?outputDataType=%22Sequence+alignment%22
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Pangenomes may be represented as graphical structures, e.g. compacted colored de Bruijn graphs, which offer a low memory usage and facilitate reference-free sequence comparisons. While sequence-to-graph mapping to graphical pangenomes has been studied for some time, no local alignment search tool in the vein of BLAST has been proposed yet. Results: We present a new heuristic method to find maximum scoring local alignments of a DNA query sequence to a pangenome represented as a compacted colored de Bruijn graph. Our approach additionally allows a comparison of similarity among sequences within the pangenome. We show that local alignment scores follow an exponential-tail distribution similar to BLAST scores, and we discuss how to estimate its parameters to separate local alignments representing sequence homology from spurious findings. An implementation of our method is presented, and its performance and usability are shown. 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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": [ "Other" ], "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/nar/gkm864", "pmid": "17947321", "pmcid": "PMC2175337", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB", "abstract": "Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs. © 2007 The Author(s).", "date": "2007-12-01T00:00:00Z", "citationCount": 5291, "authors": [ { "name": "Pruesse E." }, { "name": "Quast C." }, { "name": "Knittel K." }, { "name": "Fuchs B.M." }, { "name": "Ludwig W." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/bts252", "pmid": "22556368", "pmcid": "PMC3389763", "type": [ "Other" ], "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" } }, { "doi": "10.1016/j.jbiotec.2017.06.1198", "pmid": "28648396", "pmcid": null, "type": [ "Review" ], "version": null, "note": null, "metadata": { "title": "25 years of serving the community with ribosomal RNA gene reference databases and tools", "abstract": "SILVA (lat. forest) is a comprehensive web resource, providing services around up to date, high-quality datasets of aligned ribosomal RNA gene (rDNA) sequences from the Bacteria, Archaea, and Eukaryota domains. SILVA dates back to the year 1991 when Dr. Wolfgang Ludwig from the Technical University Munich started the integrated software workbench ARB (lat. tree) to support high-quality phylogenetic inference and taxonomy based on the SSU and LSU rDNA marker genes. At that time, the ARB project maintained both, the sequence reference datasets and the software package for data analysis. In 2005, with the massive increase of DNA sequence data, the maintenance of the software system ARB and the corresponding rRNA databases SILVA was split between Munich and the Microbial Genomics and Bioinformatics Research Group in Bremen. ARB has been continuously developed to include new features and improve the usability of the workbench. Thousands of users worldwide appreciate the seamless integration of common analysis tools under a central graphical user interface, in combination with its versatility. The first SILVA release was deployed in February 2007 based on the EMBL-EBI/ENA release 89. Since then, full SILVA releases offering the database content in various flavours are published at least annually, complemented by intermediate web-releases where only the SILVA web dataset is updated. SILVA is the only rDNA database project worldwide where special emphasis is given to the consistent naming of clades of uncultivated (environmental) sequences, where no validly described cultivated representatives are available. Also exclusive for SILVA is the maintenance of both comprehensive aligned 16S/18S rDNA and 23S/28S rDNA sequence datasets. Furthermore, the SILVA alignments and trees were designed to include Eukaryota, another unique feature among rDNA databases. With the termination of the European Ribosomal RNA Database Project in 2007, the SILVA database has become the authoritative rDNA database project for Europe. The application spectrum of ARB and SILVA ranges from biodiversity analysis, medical diagnostics, to biotechnology and quality control for academia and industry.", "date": "2017-11-10T00:00:00Z", "citationCount": 635, "authors": [ { "name": "Glockner F.O." }, { "name": "Yilmaz P." }, { "name": "Quast C." }, { "name": "Gerken J." }, { "name": "Beccati A." }, { "name": "Ciuprina A." }, { "name": "Bruns G." }, { "name": "Yarza P." }, { "name": "Peplies J." }, { "name": "Westram R." }, { "name": "Ludwig W." } ], "journal": "Journal of Biotechnology" } }, { "doi": "10.1186/s12859-017-1841-3", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SILVA tree viewer: Interactive web browsing of the SILVA phylogenetic guide trees", "abstract": "Background: Phylogenetic trees are an important tool to study the evolutionary relationships among organisms. The huge amount of available taxa poses difficulties in their interactive visualization. This hampers the interaction with the users to provide feedback for the further improvement of the taxonomic framework. Results: The SILVA Tree Viewer is a web application designed for visualizing large phylogenetic trees without requiring the download of any software tool or data files. The SILVA Tree Viewer is based on Web Geographic Information Systems (Web-GIS) technology with a PostgreSQL backend. It enables zoom and pan functionalities similar to Google Maps. The SILVA Tree Viewer enables access to two phylogenetic (guide) trees provided by the SILVA database: the SSU Ref NR99 inferred from high-quality, full-length small subunit sequences, clustered at 99% sequence identity and the LSU Ref inferred from high-quality, full-length large subunit sequences. Conclusions: The Tree Viewer provides tree navigation, search and browse tools as well as an interactive feedback system to collect any kinds of requests ranging from taxonomy to data curation and improving the tool itself.", "date": "2017-09-30T00:00:00Z", "citationCount": 29, "authors": [ { "name": "Beccati A." }, { "name": "Gerken J." }, { "name": "Quast C." }, { "name": "Yilmaz P." }, { "name": "Glockner F.O." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "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 }, { "name": "SILVA Team", "email": "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 } ], "owner": "silva", "additionDate": "2016-09-30T15:59:05Z", "lastUpdate": "2025-06-30T13:26:42.882897Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Zoonomia", "description": "The Zoonomia Project provides access to genomic data including assemblies, annotations and alignments for 240 mammalian species.", "homepage": "https://zoonomiaproject.org/", "biotoolsID": "zoonomiaproject", "biotoolsCURIE": "biotools:zoonomiaproject", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2909", "term": "Organism name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1045", "term": "Species name" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3002", "term": "Annotation track" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0925", "term": "Sequence assembly" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3050", "term": "Biodiversity" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "adriaan", "additionDate": "2025-06-16T13:44:36.983992Z", "lastUpdate": "2025-06-16T13:51:19.876113Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "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. 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], "version": null, "note": null, "metadata": { "title": "BioSurfDB: Knowledge and algorithms to support biosurfactants and biodegradation studies", "abstract": "Crude oil extraction, transportation and use provoke the contamination of countless ecosystems. Therefore, bioremediation through surfactants mobilization or biodegradation is an important subject, both economically and environmentally. Bioremediation research had a great boost with the recent advances in Metagenomics, as it enabled the sequencing of uncultured microorganisms providing new insights on surfactant-producing and/or oil-degrading bacteria. Many research studies are making available genomic data from unknown organisms obtained from metagenomics analysis of oil-contaminated environmental samples. These new datasets are presently demanding the development of new tools and data repositories tailored for the biological analysis in a context of bioremediation data analysis. This work presents BioSurfDB, www.biosurfdb.org, a curated relational information system integrating data from: (i) metagenomes; (ii) organisms; (iii) biodegradation relevant genes; proteins and their metabolic pathways; (iv) bioremediation experiments results, with specific pollutants treatment efficiencies by surfactant producing organisms; and (v) a biosurfactant-curated list, grouped by producing organism, surfactant name, class and reference. The main goal of this repository is to gather information on the characterization of biological compounds and mechanisms involved in biosurfactant production and/or biodegradation and make it available in a curated way and associated with a number of computational tools to support studies of genomic and metagenomic data.", "date": "2015-01-01T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Oliveira J.S." }, { "name": "Araujo W." }, { "name": "Sales A.I.L." }, { "name": "De Brito Guerra A." }, { "name": "Da Silva Araujo S.C." }, { "name": "De Vasconcelos A.T.R." }, { "name": "Agnez-Lima L.F." }, { "name": "Freitas A.T." } ], "journal": "Database" } } ], "credit": [ { "name": "Jorge S. 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Each of these steps requires a separate computational task and sets of tools. Currently in order to relate protein features and gene neighborhoods information to phylogeny, researchers need to prepare all the necessary data and combine them by hand, which is time-consuming and error-prone. Here, we present a new platform, TREND (tree-based exploration of neighborhoods and domains), which can perform all the necessary steps in automated fashion and put the derived information into phylogenomic context, thus making evolutionary based protein function analysis more efficient. A rich set of adjustable components allows a user to run the computational steps specific to his task. 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