Assistant Research Professor

Department: Institute for Applied AI Innovation

Dr. Khodeza Begum Mitchell is a computational scientist and bioinformatics researcher at the Institute for Applied AI Innovation (AAII) at The University of Texas at El Paso. Her research focuses on bioinformatics, machine learning, and AI-enabled biomedical knowledge discovery, including the development of biomedical databases and computational tools. Her work combines machine learning, genomic and transcriptomic analysis, and database development to investigate questions in cancer and chronic disease. She co-developed GPCR-PEnDB, a database of protein sequences and derived features that supports the prediction and classification of G protein-coupled receptors (GPCRs), and contributed to computational analysis of ligand-binding relationships across GPCR families. Her recent work includes GPCR-PEnDB 2.0, a published resource that uses AI-assisted integration of the research literature to support exploration of GPCR-cancer associations. Preliminary findings from this work were presented at the RCMI 2026 conference.

Dr. Mitchell’s collaborative research spans genomic variant prioritization, non-coding RNA expression, and molecular pathways associated with disease and treatment response. She has contributed to studies of thyroid cancer, Chagas cardiomyopathy, and an integrative variant-scoring method for identifying candidate genes associated with ovarian and thyroid cancer. Her work also includes analysis of behavioral, physiological, and inflammatory data in a university population along the U.S.-Mexico border.

Dr. Mitchell develops computational infrastructure and reproducible workflows for biological sequence analysis, genomic variant interpretation, and transcriptomics, supporting biomedical data integration and the development of searchable research resources and interactive visualizations. She also collaborates with the Integrative Analytics Unit (IAU) of the Border Biomedical Research Center (BBRC). She has delivered hands-on bioinformatics training in containerized workflows and genomic variant analysis and is a listed member of the NIH-supported DAIR³ (Data and AI Intensive Research with Rigor and Reproducibility) program.

Other Affiliations: Border Biomedical Research Center (BBRC) Integrative Analytics Unit (IAU), Computational Science Program at UTEP, Bioinformatics Program at UTEP, DAIR³ Program

Keywords of Expertise: Computational Genomics, Bioinformatics, Machine Learning, AI-Enabled Biomedical Knowledge Discovery, Data Analytics, Reproducible Research Workflows, Protein Classification.