Rate My Professor Brett McKinney

Brett McKinney, Ph.D., Warren Foundation Chair in Bioinformatics and Professor of Computer Science and Mathematics in the Tandy School of Computer Science at the University of Tulsa, holds a joint appointment in the Department of Mathematics. A native Tulsan, he completed his undergraduate studies summa cum laude in physics and mathematics at the University of Tulsa in 1996, where he was inducted into Phi Beta Kappa and participated in the honors program. McKinney earned his M.S. in physics in 1999 and Ph.D. in theoretical physics in 2003 from the University of Oklahoma. He then pursued a postdoctoral fellowship in biomathematics and computational biology at Vanderbilt University Medical Center. Before returning to the University of Tulsa, he held the position of assistant professor in the Department of Genetics at the University of Alabama at Birmingham School of Medicine. Currently, he serves as a Dean Fellow and leads the In Silico Research Group.

McKinney's research centers on the development of machine learning and artificial intelligence algorithms tailored for challenges in the biomedical and physical sciences. He has contributed key methods for detecting networks of interacting variables to create accurate and interpretable machine learning models, applied in collaborations spanning neuroscience, immunology, geochemistry, and astrobiology. His theoretical work addresses foundational aspects of quantum mechanics, such as the influence of spatial dimensionality on many-body systems including Bose-Einstein condensates. The In Silico Research Group, under his direction, employs machine learning and systems-level network models to derive insights from high-dimensional biological data, with emphasis on human immune responses to vaccines and neuropsychiatric disorders, integrating diverse data types like next-generation sequencing, transcriptomics, and MRI. In 2024, McKinney secured a NASA Established Program to Stimulate Competitive Research grant worth $750,000 over three years for the project "Biosignature Detection of Solar System Ocean Worlds using Science-Guided Machine Learning." His prominent publications encompass "Machine learning for detecting gene-gene interactions: a review" (Applied Bioinformatics, 2006; 345 citations), "A nonlinear simulation framework supports adjusting for age when analyzing BrainAGE" (Frontiers in Aging Neuroscience, 2018; 274 citations), "Consensus features nested cross-validation" (Bioinformatics, 2020; 236 citations), "Microfluidic platform for real-time signaling analysis of multiple single T cells in parallel" (Lab on a Chip, 2008; 183 citations), and "Vaccinomics, adversomics, and the immune response network theory: individualized vaccinology in the 21st century" (Seminars in Immunology, 2013; 144 citations). McKinney's scholarship has garnered over 3,892 citations on Google Scholar, exerting substantial influence in bioinformatics through advancements in epistasis analysis, feature selection, and related domains.