Difference between revisions of "Research"
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==Collaborators==  | ==Collaborators==  | ||
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*Edward Marcotte, University of Texas at Austin, USA  | *Edward Marcotte, University of Texas at Austin, USA  | ||
*Andrew Fraser, University of Toronto, Canada  | *Andrew Fraser, University of Toronto, Canada  | ||
| − | Ben Lehner, Systems Biology Unit, EMBL-CRG, Spain  | + | *Ben Lehner, Systems Biology Unit, EMBL-CRG, Spain  | 
| − | Sue Rhee, Carnegie Institution of Science, USA  | + | *Sue Rhee, Carnegie Institution of Science, USA  | 
| − | Pamela Ronald, University of California at Davis, USA  | + | *Pamela Ronald, University of California at Davis, USA  | 
| − | Matthew Hurles, Sanger Institute, UK  | + | *Matthew Hurles, Sanger Institute, UK  | 
| − | Philip Benfey, Duke University, USA  | + | *Philip Benfey, Duke University, USA  | 
| − | Sangsun Yoon, Yonsei Medical School, Korea  | + | *Sangsun Yoon, Yonsei Medical School, Korea  | 
| − | Dongryul Lee, Cha Medical School, Korea  | + | *Dongryul Lee, Cha Medical School, Korea  | 
| − | Yongsun Bahn, Yonsei University, Korea  | + | *Yongsun Bahn, Yonsei University, Korea  | 
| − | Sangjun Ha, Yonsei University, Korea  | + | *Sangjun Ha, Yonsei University, Korea  | 
==Functional Networks==  | ==Functional Networks==  | ||
Revision as of 16:09, 9 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
 - Sue 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