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Abstract
Annual Review of Genomics and Human Genetics
Vol. 6: 381-406 (Volume publication date September 2005)
(doi:10.1146/annurev.genom.6.080604.162234)
DISEASE GENE DISCOVERY THROUGH INTEGRATIVE GENOMICS

Cosmas Giallourakis,1,2 Charlotte Henson,1 Michael Reich,1 Xiaohui Xie, and1 Vamsi K. Mootha1,3,4
1Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02139;
2Gastrointestinal Unit, Massachusetts General Hospital, Boston, Massachusetts 02114;
3Department of Systems Biology, Harvard Medical School, Boston, Massachusetts 02446;
4Center for Human Genetics Research, Massachusetts General Hospital, Boston, Massachusetts 02114; email:

▪ Abstract The availability of complete genome sequences and the wealth of large-scale biological data sets now provide an unprecedented opportunity to elucidate the genetic basis of rare and common human diseases. Here we review some of the emerging genomics technologies and data resources that can be used to infer gene function to prioritize candidate genes. We then describe some computational strategies for integrating these large-scale data sets to provide more faithful descriptions of gene function, and how such approaches have recently been applied to discover genes underlying Mendelian disorders. Finally, we discuss future prospects and challenges for using integrative genomics to systematically discover not only single genes but also entire gene networks that underlie and modify human disease.

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Authors:
Cosmas Giallourakis
Charlotte Henson
Michael Reich
Xiaohui Xie
Vamsi K. Mootha
Keywords:
human genetics
positional cloning
functional genomics
machine learning

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