RCMI - DATABIOM: RCMI Data Analytics and Training for Bioinformatics, Machine Learning in Health Research Abstract Texas Southern University (TSU), one of the largest Historically Black Colleges and Universities in the United States, is in Houston, Texas, one of the most diverse cities in the United States. The rapid growth of biomedical data necessitates innovative approaches to harness its potential for precision medicine, drug discovery and development, disease diagnosis and prediction and more. This project proposes a comprehensive framework that combines advanced data analytics techniques with targeted training programs to develop proficiency in data science, bioinformatics, and machine learning to enhance institutional data science competencies on TSU campus and build institutional partnership. The overarching aim is to enhance TSU's institutional data science and research capabilities and foster institutional partnerships. Our specific aims include; 1) Enhance Human Capital Through Data Science Skills. Enhance TSU’s institutional data science and computational capacity by providing a variety of training and educational initiatives aimed at improving the data science skills of faculty, staff (including postdoctoral fellows), and students (undergraduate and postgraduate) lacking expertise in data-related fields. These training will include, but are not limited to: i) Integrated data analysis – employ innovative data analytics and bioinformatics techniques to integrate diverse datasets, including genomic, pharmacological, clinical, and health disparity information, ii) Machine learning/artificial intelligence (ML/AI) - establish specialized training programs to empower researchers, faculty, staff, and students with the skills required to navigate and leverage ML/AI tools effectively, iii) Public health data analysis - Utilize existing public health datasets in program training to evaluate health disparities and allow for hands-on training with relevant data. 2) Establish Collaborative Data Science Partnerships. Establish strategic partnerships to advance the identity of data science and foster fair data practices via cooperative research endeavors. Through the accomplishment of these specific aims, this project seeks to broaden TSU data science and capacity to advance research program and ultimately advance the field of data science. We expect that achieving these aims will expand human capital in the field of data science, enhance TSU’s data science capabilities to drive research programs forward, forge partnerships to promote the prominence of data science while advocating for equitable data practices through collaborative research efforts and striving to enhance the participation of UMCs in biomedical computing and informatics disciplines.