Advanced search
1 file | 208.16 KB Add to list
Author
Organization
Project
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.
Keywords
INFERENCE, STANDARDS, EXPRESSION, CONSERVATION, IMPLEMENTATION, SEQUENCE, GENE, EVOLUTION, HIERARCHICAL CATALOG, LIFE SCIENCES

Downloads

  • Sonnhammer et al. 2014 Bioinformatics 30 2993.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 208.16 KB

Citation

Please use this url to cite or link to this publication:

MLA
Sonnhammer, Erik LL, et al. “Big Data and Other Challenges in the Quest for Orthologs.” BIOINFORMATICS, vol. 30, no. 21, 2014, pp. 2993–98, doi:10.1093/bioinformatics/btu492.
APA
Sonnhammer, E. L., Gabaldón, T., da Silva, A. W. S., Martin, M., Robinson-Rechavi, M., Boeckmann, B., … Vandepoele, K. (2014). Big data and other challenges in the quest for orthologs. https://doi.org/10.1093/bioinformatics/btu492
Chicago author-date
Sonnhammer, Erik LL, Toni Gabaldón, Alan W Sousa da Silva, Maria Martin, Marc Robinson-Rechavi, Brigitte Boeckmann, Paul D Thomas, et al. 2014. “Big Data and Other Challenges in the Quest for Orthologs.” BIOINFORMATICS. https://doi.org/10.1093/bioinformatics/btu492.
Chicago author-date (all authors)
Sonnhammer, Erik LL, Toni Gabaldón, Alan W Sousa da Silva, Maria Martin, Marc Robinson-Rechavi, Brigitte Boeckmann, Paul D Thomas, Christine Dessimoz, the Quest Orthologs Consortium, Michiel Van Bel, and Klaas Vandepoele. 2014. “Big Data and Other Challenges in the Quest for Orthologs.” BIOINFORMATICS. doi:10.1093/bioinformatics/btu492.
Vancouver
1.
Sonnhammer EL, Gabaldón T, da Silva AWS, Martin M, Robinson-Rechavi M, Boeckmann B, et al. Big data and other challenges in the quest for orthologs. Vol. 30, BIOINFORMATICS. 2014. p. 2993–8.
IEEE
[1]
E. L. Sonnhammer et al., “Big data and other challenges in the quest for orthologs,” BIOINFORMATICS, vol. 30, no. 21. pp. 2993–2998, 2014.
@misc{5774024,
  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.}},
  author       = {{Sonnhammer, Erik LL and Gabaldón, Toni and da Silva, Alan W Sousa and Martin, Maria and Robinson-Rechavi, Marc and Boeckmann, Brigitte and Thomas, Paul D and Dessimoz, Christine and Quest Orthologs Consortium, the and Van Bel, Michiel and Vandepoele, Klaas}},
  issn         = {{1367-4803}},
  keywords     = {{INFERENCE,STANDARDS,EXPRESSION,CONSERVATION,IMPLEMENTATION,SEQUENCE,GENE,EVOLUTION,HIERARCHICAL CATALOG,LIFE SCIENCES}},
  language     = {{eng}},
  number       = {{21}},
  pages        = {{2993--2998}},
  series       = {{BIOINFORMATICS}},
  title        = {{Big data and other challenges in the quest for orthologs}},
  url          = {{http://doi.org/10.1093/bioinformatics/btu492}},
  volume       = {{30}},
  year         = {{2014}},
}

Altmetric
View in Altmetric
Web of Science
Times cited: