Research
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
