According to the most recent estimates, the number of human genes is possibly—but not certainly—between 20,000 and 25,000. To contribute strategies to reduce this uncertainty, several groups working on computational gene prediction met recently at the Welcome Trust Sanger Institute with the goal to test and compare predictive methods of genome annotation.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Optimization of multi-classifiers for computational biology: application to gene finding and expression
Theoretical Chemistry Accounts Open Access 15 October 2009
-
Quantitative measures for the management and comparison of annotated genomes
BMC Bioinformatics Open Access 23 February 2009
-
Applying negative rule mining to improve genome annotation
BMC Bioinformatics Open Access 21 July 2007
Access options
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
References
Venter, J.C. et al. Science 291, 1304–1351 (2001).
Lander, E.S. et al. Nature 409, 860–921 (2001).
Rogers, J. Cold Spring Harb. Symp. Quant. Biol. 68, 1–11 (2003).
International Human Genome Sequencing Consortium. Nature 431, 931–945 (2004).
Brent, M.R. & Guigo, R. Curr. Opin. Struct. Biol. 14, 264–272 (2004).
ENCODE Project Consortium. Science 306, 636–340 (2004).
Ashurst, J.L. & Collins, J.E. Annu. Rev. Genomics Hum. Genet. 4, 69–88 (2003).
Reese, M.G. et al. Genome Res. 10, 483–501 (2000).
Bajic, V.B. Brief Bioinform. 1, 214228 (2000).
Baldi, P., Brunak, S., Chauvin, Y., Andersen, C.A. & Nielsen, H. Bioinformatics 16, 412–424 (2000).
Burset, M. & Guigo, R. Genomics 34, 353–367 (1996).
Acknowledgements
The GENCODE annotation is mostly the effort of A. Frankish, D. Swarbreck, J. Gilbert, J. Ashurst and T. Hubbard from the Havana team at the Wellcome Trust Sanger Institute; of C. Ucla, A. Reymond and S. Antonarakis from the Faculté de Médecine Université de Genève, and of F. Denoeud, J. Lagarde and R. Guigó from the Institut Municipal d'Investigació Mèdica (IMIM) in Barcelona. P. Flicek from the European Bioinformatics Insitute and J.F. Abril from the IMIM were responsible for computing most of the accuracy measures. J. Ashurst, E. Birney, P. Good, R. Guigó and T. Hubbard participated in the organizing committee. M. Ashburner, V.B. Bajic, T. Gingeras, S. Lewis and M. Reese were members of the advisory committee. The workshop was part of the ENCODE project that is funded by the US National Institutes of Health NHGRI.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Guigó, R., Reese, M. EGASP: collaboration through competition to find human genes. Nat Methods 2, 575–577 (2005). https://doi.org/10.1038/nmeth0805-575
Issue Date:
DOI: https://doi.org/10.1038/nmeth0805-575
This article is cited by
-
Coding sequence density estimation via topological pressure
Journal of Mathematical Biology (2015)
-
A beginner's guide to eukaryotic genome annotation
Nature Reviews Genetics (2012)
-
Optimization of multi-classifiers for computational biology: application to gene finding and expression
Theoretical Chemistry Accounts (2010)
-
Quantitative measures for the management and comparison of annotated genomes
BMC Bioinformatics (2009)
-
Applying negative rule mining to improve genome annotation
BMC Bioinformatics (2007)
