ProDiGe: Prioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples

BMC Bioinformatics

Research Article

Jean-Philippe Vert¹  Fantine Mordelet² 

[1] Centre for Computational Biology, Mines ParisTech, F-77300, Fontainebleau, France;Institut Curie, F-75248, Paris, France;U900, INSERM, F-75248, Paris, France;Centre for Computational Biology, Mines ParisTech, F-77300, Fontainebleau, France;Institut Curie, F-75248, Paris, France;U900, INSERM, F-75248, Paris, France;CREST, INSEE, F-92240, Malakoff, France;

关键词: Disease Gene;    Multiple Kernel Learning;    Orphan Disease;    Gene Prioritization;    Multitask Learning;   

DOI  :  10.1186/1471-2105-12-389

 received in 2011-06-23, accepted in 2011-10-06,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundElucidating 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.ResultsWe propose ProDiGe, a novel algorithm for Prioritization of Disease Genes. ProDiGe implements a novel machine learning strategy based on learning from positive and unlabeled examples, which allows to integrate various sources of information about the genes, to share information about known disease genes across diseases, and to perform genome-wide searches for new disease genes. Experiments on real data show that ProDiGe outperforms state-of-the-art methods for the prioritization of genes in human diseases.ConclusionsProDiGe implements a new machine learning paradigm for gene prioritization, which could help the identification of new disease genes. It is freely available at http://cbio.ensmp.fr/prodige.

【 授权许可】

CC BY   
© Mordelet and Vert; licensee BioMed Central Ltd. 2011