Computational systems biology  
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Causal Pathways from Genotype to Phenotype

Elucidating causal pathways bridging genotype and phenotype is one of the fundamental challenges in genetic and genomic research. Gene variants that control phenotypes are typically discovered by combined linkage analysis and molecular validation. However, these genotype-phenotype associations do not expose the underlying causal pathways through which gene variants operate on phenotypes. We are exploring genomic and computational approaches to uncover the causal pathways through which genetic loci influence phenotypes and predict the effects of genetic and transcriptional variations/interventions on gene expression and physiological/behavioral phenotypes of individuals with different genetic backgrounds. We believe research towards this direction will ultimately lead to the development of the computational methods that enable personalized predictive genetics and medicine.

Functional Effects of Genetic and Somatic mutations

There has been great expectation that knowledge of an individual’s genotype will provide a basis for assessing susceptibility to diseases and designing individualized therapy. Vast majority of sequence variants in humans are differences in single bases of DNA, called single nucleotide polymorphisms. Nonsynonymous single nucleotide polymorphisms (nsSNP) that lead to an amino acid change in the protein product are of particular interest because they account for nearly half of the known genetic variations related to human inherited diseases. We investigate the correlations between selective constraint, structural environments and functional impacts of non-synonymous single nucleotide polymorphisms (nsSNPs) and develop computational methods to predict the phenotypic effects of snsSNPs. We also study the functional effects of genetic polymorphisms and cancer somatic mutations in the non-coding regions such as microRNAs and their target sites.