EGGSlicer: predicting biologically meaningful gene sets from gene clusters using gene ontology information
Pages 448 - 450
Abstract
Predicting conserved gene sets in genome is a very important problem and there are a number of algorithms developed for the task. Unfortunately, conserved gene cluster prediction results depend largely on the phylogenetic distance of genomes. In particular, the sizes of clusters for closely related genomes are large and the functions of these genes in each cluster are diverse. Due to the vast diversity in the functions of these genes, it is difficult to define the precise biological meaning of those genes. To address this problem, we have developed a comparative genomics approach to splitting large conserved gene clusters into functionally related sub-clusters using gene ontology information.
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- EGGSlicer: predicting biologically meaningful gene sets from gene clusters using gene ontology information
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Published In
August 2010
705 pages
ISBN:9781450304382
DOI:10.1145/1854776
- General Chairs:
- Aidong Zhang,
- Mark Borodovsky,
- Program Chairs:
- Gultekin Ozsoyoglu,
- Armin Mikler
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Published: 02 August 2010
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BCB'10: ACM International Conference on Bioinformatics and Computational Biology
August 2 - 4, 2010
New York, Niagara Falls
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