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Consensus phylogenies based on the bootstrap and other resampling methods play a crucial part in analyzing the robustness of the trees produced for these analyses. Methodology: Our focus was to increase the number of bootstrap replications that can be performed on large protein datasets using the maximum parsimony, distance matrix, and maximum likelihood methods. We have modified the PHYLIP package using MPI to enable large-scale phylogenetic study of protein sequences, using a statistically robust number of bootstrapped datasets, to be performed in a moderate amount of time. This paper discusses the methodology used to parallelize the PHYLIP programs and reports the performance of the parallel PHYLIP programs that are relevant to the study of protein evolution on several protein datasets. Conclusions: Calculations that currently take a few days on a state of the art desktop workstation are reduced to calculations that can be performed over lunchtime on a modern parallel computer. 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From aligned sequences, (optionally) phylogenetic trees can be inferred using FastTree or RAxML.","cmd":null}],"toolType":["Web application","Database portal"],"topic":[{"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_3293","term":"Phylogenetics"},{"uri":"http://edamontology.org/topic_0637","term":"Taxonomy"},{"uri":"http://edamontology.org/topic_3050","term":"Biodiversity"},{"uri":"http://edamontology.org/topic_3301","term":"Microbiology"},{"uri":"http://edamontology.org/topic_0632","term":"Probes and primers"}],"operatingSystem":[],"language":[],"license":"CC-BY-4.0","collectionID":["de.NBI","de.NBI-biodata","DSMZ Digital Diversity"],"maturity":"Mature","cost":"Free of charge","accessibility":"Open access","elixirPlatform":["Data"],"elixirNode":["Germany"],"elixirCommunity":[],"link":[{"url":"https://www.arb-silva.de/browser/","type":["Service"],"note":"SILVA Taxonomy Browser"},{"url":"https://www.arb-silva.de/search/","type":["Service"],"note":"SILVA metadata search"},{"url":"https://www.arb-silva.de/aligner/","type":["Service"],"note":"ACT: Alignment, Classification and Tree Service"},{"url":"https://www.arb-silva.de/search/testprobe/","type":["Service"],"note":"SILVA Probe Match and Evaluation Tool"},{"url":"https://www.arb-silva.de/search/testprime/","type":["Service"],"note":"SILVA Primer Evaluation Tool"},{"url":"https://treeviewer.arb-silva.de/","type":["Service"],"note":"Web-based viewer for the SILVA guide trees"}],"download":[{"url":"https://www.arb-silva.de/download/archive/","type":"Downloads page","note":"SILVA dataset archive","version":null}],"documentation":[{"url":"https://www.arb-silva.de/silva-license-information/","type":["Terms of use"],"note":null},{"url":"https://www.arb-silva.de/contact/","type":["Citation instructions"],"note":null},{"url":"https://www.arb-silva.de/documentation/","type":["General"],"note":null},{"url":"https://www.arb-silva.de/documentation/faqs/","type":["FAQ"],"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":["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":"BioSimulations","description":"BioSimulations is a web application for sharing and re-using biomodels, simulations, and visualizations of simulations results. BioSimulations supports a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical modeling), model formats (e.g., BNGL, CellML, SBML), and simulation tools (e.g., COPASI, libRoadRunner/tellurium, NFSim, VCell). BioSimulations aims to help researchers discover published models that might be useful for their research and quickly try them via a simple web-based interface.","homepage":"https://www.biosimulations.org/","biotoolsID":"biosimulations","biotoolsCURIE":"biotools:biosimulations","version":[],"otherID":[{"value":"RRID:SCR_018733","type":"rrid","version":null}],"relation":[{"biotoolsID":"runbiosimulations","type":"uses"},{"biotoolsID":"biosimulators","type":"uses"},{"biotoolsID":"biomodels","type":"uses"},{"biotoolsID":"sbml","type":"uses"},{"biotoolsID":"bionetgen","type":"uses"},{"biotoolsID":"cobrapy","type":"uses"},{"biotoolsID":"copasi","type":"uses"},{"biotoolsID":"libroadrunner","type":"uses"}],"function":[{"operation":[{"uri":"http://edamontology.org/operation_0337","term":"Visualisation"},{"uri":"http://edamontology.org/operation_2426","term":"Modelling and simulation"}],"input":[{"data":{"uri":"http://edamontology.org/data_0950","term":"Mathematical 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from both bacteria and archaea and provides a basis for IS classification. Each IS is indexed in ISfinder with various associated pieces of information and classified into a group or family to provide some insight into its phylogeny.","homepage":"http://www-is.biotoul.fr","biotoolsID":"isfinder","biotoolsCURIE":"biotools:isfinder","version":[],"otherID":[{"value":"RRID:SCR_003020","type":"rrid","version":null}],"relation":[],"function":[{"operation":[{"uri":"http://edamontology.org/operation_3211","term":"Genome indexing"},{"uri":"http://edamontology.org/operation_3349","term":"Bibliography generation"},{"uri":"http://edamontology.org/operation_2436","term":"Gene-set enrichment analysis"}],"input":[],"output":[],"note":null,"cmd":null}],"toolType":["Database portal"],"topic":[{"uri":"http://edamontology.org/topic_3068","term":"Literature and language"},{"uri":"http://edamontology.org/topic_0084","term":"Phylogeny"},{"uri":"http://edamontology.org/topic_0798","term":"Mobile genetic elements"},{"uri":"http://edamontology.org/topic_0621","term":"Model organisms"},{"uri":"http://edamontology.org/topic_3168","term":"Sequencing"}],"operatingSystem":["Linux","Windows","Mac"],"language":["SQL"],"license":null,"collectionID":[],"maturity":null,"cost":null,"accessibility":null,"elixirPlatform":["Tools"],"elixirNode":["France"],"elixirCommunity":[],"link":[],"download":[],"documentation":[{"url":"https://www-is.biotoul.fr/general_information.php","type":["General"],"note":null}],"publication":[{"doi":"10.1093/nar/gkp947","pmid":"19906702","pmcid":"PMC2808865","type":[],"version":null,"note":null,"metadata":{"title":"ISbrowser: An extension of ISfinder for visualizing insertion sequences in prokaryotic genomes","abstract":"Insertion sequences (ISs) are among the smallest and simplest autonomous transposable elements. ISfinder (http://www-is.biotoul.fr/) is a dedicated IS database which assigns names to individual ISs to maintain a coherent nomenclature, an IS repository including >3000 individual ISs from both bacteria and archaea and provides a basis for IS classification. Each IS is indexed in ISfinder with various associated pieces of information (the complete nucleotide sequence, the sequence of the ends and target sites, potential open reading frames, strain of origin, distribution in other strains and available bibliography) and classified into a group or family to provide some insight into its phylogeny. ISfinder also includes extensive background information on ISs and transposons in general. Online tools are gradually being added. At present, it is difficult to visualize the global distribution of ISs in a given bacterial genome. Such information would facilitate understanding of the impact of these small transposable elements on shaping their host genome. Here we describe ISbrowser (http://www-genome.biotoul.fr/ISbrowser.php), an extension to the ISfinder platform and a tool which permits visualization of the position, orientation and distribution of complete and partial ISs in individual prokaryotic genomes. © The Author(s) 2009. Published by Oxford University Press.","date":"2009-11-11T00:00:00Z","citationCount":43,"authors":[{"name":"Kichenaradja P."},{"name":"Siguier P."},{"name":"Perochon J."},{"name":"Chandler M."}],"journal":"Nucleic Acids Research"}}],"credit":[{"name":"Patricia Siguier","email":"Patricia.Siguier@ibcg.biotoul.fr","url":null,"orcidid":null,"gridid":null,"rorid":null,"fundrefid":null,"typeEntity":"Person","typeRole":["Primary contact"],"note":null}],"owner":"Patricia_SIguier","additionDate":"2017-03-27T07:19:58Z","lastUpdate":"2025-01-24T09:59:36.949842Z","editPermission":{"type":"group","authors":["Patricia_SIguier"]},"validated":1,"homepage_status":0,"elixir_badge":0,"confidence_flag":null},{"name":"Pharos","description":"Pharos is the web interface for data collected by the Illuminating the Druggable Genome initiative. Target, disease and ligand information are collected and displayed.\n\nYou are using an outdated browser. Please upgrade your browser to improve your experience.","homepage":"https://pharos.nih.gov/","biotoolsID":"pharos","biotoolsCURIE":"biotools:pharos","version":[],"otherID":[{"value":"RRID: SCR_016924","type":"rrid","version":null}],"relation":[],"function":[{"operation":[{"uri":"http://edamontology.org/operation_3436","term":"Aggregation"},{"uri":"http://edamontology.org/operation_0337","term":"Visualisation"},{"uri":"http://edamontology.org/operation_2422","term":"Data retrieval"}],"input":[],"output":[],"note":null,"cmd":null}],"toolType":[],"topic":[{"uri":"http://edamontology.org/topic_0121","term":"Proteomics"},{"uri":"http://edamontology.org/topic_0625","term":"Genotype and phenotype"},{"uri":"http://edamontology.org/topic_0080","term":"Sequence analysis"},{"uri":"http://edamontology.org/topic_0634","term":"Pathology"},{"uri":"http://edamontology.org/topic_3474","term":"Machine learning"}],"operatingSystem":[],"language":[],"license":null,"collectionID":[],"maturity":null,"cost":null,"accessibility":null,"elixirPlatform":[],"elixirNode":[],"elixirCommunity":[],"link":[],"download":[],"documentation":[{"url":"https://pharos.nih.gov/api","type":["API documentation"],"note":null}],"publication":[{"doi":"10.1093/nar/gkaa993","pmid":"33156327","pmcid":"PMC7778974","type":[],"version":null,"note":null,"metadata":{"title":"TCRD and Pharos 2021: Mining the human proteome for disease biology","abstract":"In 2014, the National Institutes of Health (NIH) initiated the Illuminating the Druggable Genome (IDG) program to identify and improve our understanding of poorly characterized proteins that can potentially be modulated using small molecules or biologics. Two resources produced from these efforts are: The Target Central Resource Database (TCRD) (http://juniper.health.unm.edu/tcrd/) and Pharos (https://pharos.nih.gov/), a web interface to browse the TCRD. The ultimate goal of these resources is to highlight and facilitate research into currently understudied proteins, by aggregating a multitude of data sources, and ranking targets based on the amount of data available, and presenting data in machine learning ready format. Since the 2017 release, both TCRD and Pharos have produced two major releases, which have incorporated or expanded an additional 25 data sources. Recently incorporated data types include human and viral-human protein-protein interactions, protein-disease and protein-phenotype associations, and drug-induced gene signatures, among others. 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