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      The EMBL-EBI search and sequence analysis tools APIs in 2019

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          Abstract

          The EMBL-EBI provides free access to popular bioinformatics sequence analysis applications as well as to a full-featured text search engine with powerful cross-referencing and data retrieval capabilities. Access to these services is provided via user-friendly web interfaces and via established RESTful and SOAP Web Services APIs ( https://www.ebi.ac.uk/seqdb/confluence/display/JDSAT/EMBL-EBI+Web+Services+APIs+-+Data+Retrieval). Both systems have been developed with the same core principles that allow them to integrate an ever-increasing volume of biological data, making them an integral part of many popular data resources provided at the EMBL-EBI. Here, we describe the latest improvements made to the frameworks which enhance the interconnectivity between public EMBL-EBI resources and ultimately enhance biological data discoverability, accessibility, interoperability and reusability.

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          Improved tools for biological sequence comparison.

          W R Pearson, D J Lipman (1988)
          We have developed three computer programs for comparisons of protein and DNA sequences. They can be used to search sequence data bases, evaluate similarity scores, and identify periodic structures based on local sequence similarity. The FASTA program is a more sensitive derivative of the FASTP program, which can be used to search protein or DNA sequence data bases and can compare a protein sequence to a DNA sequence data base by translating the DNA data base as it is searched. FASTA includes an additional step in the calculation of the initial pairwise similarity score that allows multiple regions of similarity to be joined to increase the score of related sequences. The RDF2 program can be used to evaluate the significance of similarity scores using a shuffling method that preserves local sequence composition. The LFASTA program can display all the regions of local similarity between two sequences with scores greater than a threshold, using the same scoring parameters and a similar alignment algorithm; these local similarities can be displayed as a "graphic matrix" plot or as individual alignments. In addition, these programs have been generalized to allow comparison of DNA or protein sequences based on a variety of alternative scoring matrices.
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            Performance, Accuracy, and Web Server for Evolutionary Placement of Short Sequence Reads under Maximum Likelihood

            Simon A Berger, Denis Krompass, Alexandros Stamatakis (2011)
            We present an evolutionary placement algorithm (EPA) and a Web server for the rapid assignment of sequence fragments (short reads) to edges of a given phylogenetic tree under the maximum-likelihood model. The accuracy of the algorithm is evaluated on several real-world data sets and compared with placement by pair-wise sequence comparison, using edit distances and BLAST. We introduce a slow and accurate as well as a fast and less accurate placement algorithm. For the slow algorithm, we develop additional heuristic techniques that yield almost the same run times as the fast version with only a small loss of accuracy. When those additional heuristics are employed, the run time of the more accurate algorithm is comparable with that of a simple BLAST search for data sets with a high number of short query sequences. Moreover, the accuracy of the EPA is significantly higher, in particular when the sample of taxa in the reference topology is sparse or inadequate. Our algorithm, which has been integrated into RAxML, therefore provides an equally fast but more accurate alternative to BLAST for tree-based inference of the evolutionary origin and composition of short sequence reads. We are also actively developing a Web server that offers a freely available service for computing read placements on trees using the EPA.
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              Programmatic access to bioinformatics tools from EMBL-EBI update: 2017

              Szymon Chojnacki, Andrew Cowley, Joon Lee … (2017)
              Abstract Since 2009 the EMBL-EBI provides free and unrestricted access to several bioinformatics tools via the user's browser as well as programmatically via Web Services APIs. Programmatic access to these tools, which is fundamental to bioinformatics, is increasingly important as more high-throughput data is generated, e.g. from proteomics and metagenomic experiments. Access is available using both the SOAP and RESTful approaches and their usage is reviewed regularly in order to ensure that the best, supported tools are available to all users. We present here an update describing the latest enhancement to the Job Dispatcher APIs as well as the governance under it.
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                Author and article information

                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 (Print): 02 July 2019
                Publication date (Electronic): 12 April 2019
                Publication date PMC-release: 12 April 2019
                Volume: 47
                Issue: W1
                Pages: W636-W641
                Affiliations
                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
                http://orcid.org/0000-0003-4208-4102
                http://orcid.org/0000-0001-8626-2148
                Article
                Publisher ID: gkz268
                DOI: 10.1093/nar/gkz268
                PMC ID: 6602479
                PubMed ID: 30976793
                SO-VID: d26dc755-7d32-47c0-aa23-0256e460803f
                Copyright © © The Author(s) 2019. 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 ( http://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 : 03 April 2019
                Date revision received : 22 March 2019
                Date received : 31 January 2019
                Page count
                Pages: 6
                Funding
                Funded by: European Molecular Biology Laboratory 10.13039/100013060
                Award ID: 654039
                Categories
                Subject: Web Server Issue

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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