ProDiGe: Prioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples
Open Access
- 6 October 2011
- journal article
- research article
- Published by Springer Science and Business Media LLC in BMC Bioinformatics
- Vol. 12 (1), 389
- https://doi.org/10.1186/1471-2105-12-389
Abstract
Elucidating the genetic basis of human diseases is a central goal of genetics and molecular biology. While traditional linkage analysis and modern high-throughput techniques often provide long lists of tens or hundreds of disease gene candidates, the identification of disease genes among the candidates remains time-consuming and expensive. Efficient computational methods are therefore needed to prioritize genes within the list of candidates, by exploiting the wealth of information available about the genes in various databases.Keywords
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