My research group’s broad research interest lies in in the development of computational tools and algorithms and also the integration and analysis of different kinds of large-scale genomic datasets to facilitate a better understanding of Mendelian disease biology. As a part of Baylor-Hopkins Center for Mendelian Genomics (CMG), our efforts have been mainly focused on developing novel computational tools that enhance discovery of novel disease genes underlying Mendelian phenotypes due to either production of truncated or altered proteins or small and intragenic copy number variant (CNV) deletions. In addition, we are co-leading another project that added a new arm of recruitment of unsolved clinical exomes from Baylor Genetics Laboratories into the research environment and designing different analytical and ancillary approaches and tools to increase the molecular diagnosis yield of unsolved clinical exomes and accelerate novel disease gene discovery. We are also working on studying alternative population substructures to elucidate the molecular mechanisms and genomic architecture underlying disease populations and Mendelian disease traits. As outlined above, my research group facilitates an improved understanding of the relationship between gene function and human phenotypes and fascinating yet understudied genetic mechanisms of disease in Mendelian disease biology through performing integrative analysis of various kinds of genomic datasets and developing computational tools, analytical frameworks and machine learning algorithms. Furthermore, we will extend those analyses and tools helping to advance gene function and genetic principles knowledge in Mendelian disease biology to unraveling the complexities of genetic mechanisms in common and complex disease traits.