Research
From Bioinformatics Lab
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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 Highlight
- 2011 Nature Reviews Genetics, Research highlight (Predicting genetic interaction)
- 2008 Bioessay, What the papers say (WormNet)
- 2008 Genome Biology, Minireview (WormNet)
- 2008 Nature methods, Research highlight (WormNet)
- 2008 Nature Genetics coverstory (WormNet): Network perturbation predicts phenotype