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Big data and other challenges in the quest for orthologs
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. He...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201156/ https://www.ncbi.nlm.nih.gov/pubmed/25064571 http://dx.doi.org/10.1093/bioinformatics/btu492 |
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author | Sonnhammer, Erik L.L. Gabaldón, Toni Sousa da Silva, Alan W. Martin, Maria Robinson-Rechavi, Marc Boeckmann, Brigitte Thomas, Paul D. Dessimoz, Christophe |
author_facet | Sonnhammer, Erik L.L. Gabaldón, Toni Sousa da Silva, Alan W. Martin, Maria Robinson-Rechavi, Marc Boeckmann, Brigitte Thomas, Paul D. Dessimoz, Christophe |
author_sort | Sonnhammer, Erik L.L. |
collection | PubMed |
description | 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@scilifelab.se or c.dessimoz@ucl.ac.uk |
format | Online Article Text |
id | pubmed-4201156 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-42011562014-10-22 Big data and other challenges in the quest for orthologs Sonnhammer, Erik L.L. Gabaldón, Toni Sousa da Silva, Alan W. Martin, Maria Robinson-Rechavi, Marc Boeckmann, Brigitte Thomas, Paul D. Dessimoz, Christophe Bioinformatics Editorial 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@scilifelab.se or c.dessimoz@ucl.ac.uk Oxford University Press 2014-11-01 2014-07-26 /pmc/articles/PMC4201156/ /pubmed/25064571 http://dx.doi.org/10.1093/bioinformatics/btu492 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/),which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Editorial Sonnhammer, Erik L.L. Gabaldón, Toni Sousa da Silva, Alan W. Martin, Maria Robinson-Rechavi, Marc Boeckmann, Brigitte Thomas, Paul D. Dessimoz, Christophe Big data and other challenges in the quest for orthologs |
title | Big data and other challenges in the quest for orthologs |
title_full | Big data and other challenges in the quest for orthologs |
title_fullStr | Big data and other challenges in the quest for orthologs |
title_full_unstemmed | Big data and other challenges in the quest for orthologs |
title_short | Big data and other challenges in the quest for orthologs |
title_sort | big data and other challenges in the quest for orthologs |
topic | Editorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201156/ https://www.ncbi.nlm.nih.gov/pubmed/25064571 http://dx.doi.org/10.1093/bioinformatics/btu492 |
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