Difference between revisions of "Research"
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==Research Philosophy== | ==Research Philosophy== | ||
| − | '''4P Research''' | + | '''4P Research (Play, Ponder, Pride, Provide)''' |
*'''Play''': Your lab must be your playground. | *'''Play''': Your lab must be your playground. | ||
*'''Ponder''': More thinking, Less labor. | *'''Ponder''': More thinking, Less labor. | ||
Revision as of 20:33, 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.
Research Philosophy
4P Research (Play, Ponder, Pride, Provide)
- Play: Your lab must be your playground.
- Ponder: More thinking, Less labor.
- Pride: Be proud of yourself and your work.
- Provide: People supported your work, thus you must return your discovery to people.
If science is good, scientists must be happy whether they are successful or not.
The more learn, the less know.
Sharing credit will convert your competitors to your collaborators.
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
