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      Big data and other challenges in the quest for orthologs

      editorial

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          Abstract

          Given the rapid increase of species with a sequenced genome, the need to identify orthologous genes between them has emerged as a central bioinformatics task. Many different methods exist for orthology detection, which makes it difficult to decide which one to choose for a particular application.

          Here, we review the latest developments and issues in the orthology field, and summarize the most recent results reported at the third ‘Quest for Orthologs’ meeting. We focus on community efforts such as the adoption of reference proteomes, standard file formats and benchmarking. Progress in these areas is good, and they are already beneficial to both orthology consumers and providers. However, a major current issue is that the massive increase in complete proteomes poses computational challenges to many of the ortholog database providers, as most orthology inference algorithms scale at least quadratically with the number of proteomes.

          The Quest for Orthologs consortium is an open community with a number of working groups that join efforts to enhance various aspects of orthology analysis, such as defining standard formats and datasets, documenting community resources and benchmarking.

          Availability and implementation: All such materials are available at http://questfororthologs.org.

          Contact: erik.sonnhammer@ 123456scilifelab.se or c.dessimoz@ 123456ucl.ac.uk

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          Most cited references46

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          Horizontal gene transfer in eukaryotic evolution.

          Horizontal gene transfer (HGT; also known as lateral gene transfer) has had an important role in eukaryotic genome evolution, but its importance is often overshadowed by the greater prevalence and our more advanced understanding of gene transfer in prokaryotes. Recurrent endosymbioses and the generally poor sampling of most nuclear genes from diverse lineages have also complicated the search for transferred genes. Nevertheless, the number of well-supported cases of transfer from both prokaryotes and eukaryotes, many with significant functional implications, is now expanding rapidly. Major recent trends include the important role of HGT in adaptation to certain specialized niches and the highly variable impact of HGT in different lineages.
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            Reorganizing the protein space at the Universal Protein Resource (UniProt)

            The mission of UniProt is to support biological research by providing a freely accessible, stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces. UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. A key development at UniProt is the provision of complete, reference and representative proteomes. UniProt is updated and distributed every 4 weeks and can be accessed online for searches or download at http://www.uniprot.org.
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              Distinguishing homologous from analogous proteins.

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                Author and article information

                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                bioinfo
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                01 November 2014
                26 July 2014
                26 July 2014
                : 30
                : 21
                : 2993-2998
                Affiliations
                1Stockholm Bioinformatics Center, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden, 2Swedish eScience Research Center, Stockholm, 3Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, 4Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain, 5Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, 6Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain, 7EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, UK, 8Department of Ecology and Evolution, University of Lausanne, 9Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, 10SwissProt, Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland, 11Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA and 12Department of Genetics, Evolution and Environment, and Department of Computer Science, University College London, Gower St, London WC1E 6BT, UK
                Author notes
                *To whom correspondence should be addressed.

                Associate Editor: John Hancock

                The member list of the Quest for Orthologs consortium is provided in the Acknowledgement section.

                Article
                btu492
                10.1093/bioinformatics/btu492
                4201156
                25064571
                08f2e878-a733-4921-84f2-87423b00c755
                © The Author 2014. Published by Oxford University Press.

                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
                : 16 April 2014
                : 25 June 2014
                : 16 July 2014
                Page count
                Pages: 6
                Categories
                Editorial
                Genome Analysis

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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