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      Search and sequence analysis tools services from EMBL-EBI in 2022

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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.

          Graphical Abstract

          Graphical Abstract

          Overview of the tools and data resources provided by EBI Search and Job Dispatcher services accessible via their webpage and programmatic interfaces.

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          Most cited references33

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          BLAST+: architecture and applications

          Christiam Camacho, George Coulouris, Vahram Avagyan … (2009)
          Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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            UniProt: the universal protein knowledgebase in 2021

            (2020)
            Abstract The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.
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              AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

              Mihaly Varadi, Stephen Anyango, Mandar Deshpande … (2021)
              The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk ) is an openly accessible, extensive database of high-accuracy protein-structure predictions. Powered by AlphaFold v2.0 of DeepMind, it has enabled an unprecedented expansion of the structural coverage of the known protein-sequence space. AlphaFold DB provides programmatic access to and interactive visualization of predicted atomic coordinates, per-residue and pairwise model-confidence estimates and predicted aligned errors. The initial release of AlphaFold DB contains over 360,000 predicted structures across 21 model-organism proteomes, which will soon be expanded to cover most of the (over 100 million) representative sequences from the UniRef90 data set.
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                Author and article information

                Contributors
                Fábio Madeira:
                ORCID: https://orcid.org/0000-0001-8728-9449
                Matt Pearce:
                ORCID: https://orcid.org/0000-0001-7037-2422
                Adrian R N Tivey
                Prasad Basutkar
                Joon Lee
                Ossama Edbali
                Nandana Madhusoodanan
                Anton Kolesnikov
                Rodrigo Lopez:
                ORCID: https://orcid.org/0000-0003-1256-7306
                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date Collection: 05 July 2022
                Publication date (Electronic): 12 April 2022
                Publication date PMC-release: 12 April 2022
                Volume: 50
                Issue: W1
                Pages: W276-W279
                Affiliations
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus , Hinxton, Cambridge CB10 1SD, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus , Hinxton, Cambridge CB10 1SD, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus , Hinxton, Cambridge CB10 1SD, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus , Hinxton, Cambridge CB10 1SD, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus , Hinxton, Cambridge CB10 1SD, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus , Hinxton, Cambridge CB10 1SD, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus , Hinxton, Cambridge CB10 1SD, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus , Hinxton, Cambridge CB10 1SD, UK
                European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus , Hinxton, Cambridge CB10 1SD, UK
                Author notes
                To whom correspondence should be addressed. Tel: +44 1223 494 423; Fax: +44 1223 494 468; Email: rls@ 123456ebi.ac.uk

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.

                Author information
                https://orcid.org/0000-0001-8728-9449
                https://orcid.org/0000-0001-7037-2422
                https://orcid.org/0000-0003-1256-7306
                Article
                Publisher ID: gkac240
                DOI: 10.1093/nar/gkac240
                PMC ID: 9252731
                PubMed ID: 35412617
                SO-VID: 6eb92bea-92b5-4f81-9ef8-21cb1c2acbcc
                Copyright © © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date accepted : 28 March 2022
                Date received : 04 February 2022
                Page count
                Pages: 4
                Funding
                Funded by: EMBL-EBI, DOI 10.13039/100012116;
                Award ID: 824087
                Funded by: BY-COVID;
                Award ID: 101046203
                Funded by: EarlyCause;
                Award ID: 848158
                Categories
                Subject: AcademicSubjects/SCI00010
                Subject: Web Server Issue

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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