Difference between revisions of "Research"

Revision as of 17:15, 10 April 2011

Research Summary

The ultimate goal of biological research is to manipulate traits that are important for medicine, agriculture, and bio-industry. This challenging task first requires good understanding of association between genotype and phenotype. Because of high complexity of genotype as well as phenotype, complexity of the genotype-phenotype association could be even untouchable by combinatorial explosion of the number of possible associations. Therefore, modern genetics needs to be more systematic and predictive. Recently we proposed network-guided approach for genetics of complex traits. First, we construct probabilistic functional gene networks for cells or organisms by benchmarking and integrating heterogeneous multi-omics data that are in general publicly available. Then, using guilt-by-association, and other algorithms of network propagation of known biological information, we predict gene functions, phenotypic effect of loss-of-function, and epistatic interaction. The information can contribute to reconstruction of map between genotype and phenotype. The network-guided genetics method has been effectively applied for various organisms; from simple microbe yeast, to multicellular animal C. elegans, to the reference plant Arabidopsis, to the reference crop rice, and to the human.

Collaborators

• Edward Marcotte, University of Texas at Austin, USA
• Andrew Fraser, University of Toronto, Canada
• Ben Lehner, Systems Biology Unit, EMBL-CRG, Spain
• Rhee, Carnegie Institution of Science, USA
• Pamela Ronald, University of California at Davis, USA
• Matthew Hurles, Sanger Institute, UK
• Philip Benfey, Duke University, USA
• Sangsun Yoon, Yonsei Medical School, Korea
• Dongryul Lee, Cha Medical School, Korea
• Yongsun Bahn, Yonsei University, Korea
• Sangjun Ha, Yonsei University, Korea

Functional Networks