Developing a Certificate in Computational Genomics and Biomedical Data Science - This project’s main objective is to put forth an undergraduate program titled “Developing a Certificate in Computational Genomics and Biomedical Data Science” (CGBDS) at the Texas Undergraduate Medical Academy (UMA) on the campus of Prairie View A&M University, a member institution of the Texas A&M University System. It hereby responds to the RFA-HG-23-002 “Broadening Opportunities for Computational Genomics and Data Science Education'' by providing prospective students with basic knowledge and skills to pursue a rewarding career in the health care practice and/ or research. The proposed curriculum underpinning this certificate is structured into four interconnected courses: Computational Genomics (CoGen), Biomedical Data Science (BiDaS), Biostatistics/ Biomathematics (StaMa), and Bioinformatics (Binfo). CoGen and BiDaS syllabi will be correlated to deal simultaneously with genomic and biomedical aspects of the same human diseases. While StaMa and Bionfo will help students learn and exercise handling and processing data from the aforementioned human diseases. Moreover, these courses will comprise practical sessions that will be organized in the fully equipped UMA laboratories for bioinformatics, genomics, and molecular and cellular b iology experiments. During this program, we will train the students on how to use NIH-supported cloud computing resources, particularly NHGRI AnVIL (Genomic Data Science Analysis, Visualization, and Informatics Lab-space). Genomic and biomedical data for training exercises will be downloaded from publicly accessible NIHcurated repositories including but not limited to: NIH National Cancer Institute Genomic Data Commons Data Portal, eMERGE (Electronic and MEdical Records and Genomics Project), PAGE (Population Architecture Using Genomics and Epidemiology), and Convergent Neuro Consortium.Thus, these courses aim to help the students understand what genomic and medical big data are, how they have been generated, how to interpret them, and how to use them for predicting further implications. To this end, these courses will be delivered by four very experienced UMA faculty. These faculty members are cognoscible in their respective fields. These courses will be integrated within the curriculum of the school of public health and eventually as the foundation for a degree in Health bioinformatics.
