Our research lies at the interface of human genetics, computational statistics, and data science. Current research focuses on understanding diverse behaviors of cells using machine learning, network science and dynamical system analysis. We develop analytical frameworks to study single-cell transcriptome data from various types of cells. We also study the genetic basis of phenotypic variability or randomness in the human population and develop computational tools to identify genetic variants that control complex traits and determine the susceptibility of genetic disorders.

selected publications
Academic Articles61
  • Cai, J. J. (2011). Evolutionary Bioinformatics with a Scientific Computing Environment. Yang, N. S. (Eds.), Systems and Computational Biology - Bioinformatics and Computational Modeling. InTech.
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Conference Papers1
chaired theses and dissertations
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mailing address
MS 4458; Veterinary Integrative Biosciences; 4458 TAMU
College Station, Texas 77843