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Liming Liang, Ph.D.

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Overview
My group focuses on developing the computational and statistical tools for analyses of multi-omics data to understand the biological mechanism for diseases and provide prediction model to assess future risk and individual benefit for intervention. We are currently looking for dedicated students (MS or PHD) for the following projects:

(1) Polygenic risk prediction model for complex diseases and traits applicable to multiple populations. The method will be evaluated and applied to biobank scale genome-wide association studies from European, African and Asian populations.

(2) Estimation of shared genetic components between complex diseases and traits by incorporating data of common and rare variants from multiple populations.

(3) Metabolomic network analysis for diseases and dietary exposure using targeted and untargeted metabolites from mass-spectrometry based metabolomics data.

(4) DNA methylation signature for aging and risk for childhood diseases (obesity and asthma) and its interaction with intervention and environmental exposures.

(5) Mapping of genetic variants for gene expression, methylation, metabolomics and other secondary traits (QTL mapping). Causal inference based on robust Mendelian randomization framework under different genetic architectures.

We actively apply these methods to large scale studies and unique longitudinal cohorts focus on Asthma, Allergy, Lung Cancer, COPD, Age-Related Macular Degeneration (AMD), Diabetes, Heart Diseases and other cardiometabolic traits with study subjects from European, African, Hispanic and Asian populations.

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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.