Philip Romero
Assistant Professor of Biomedical Engineering
Dr. Romero’s research group develops data-driven approaches to dissect the molecular basis of protein function and engineer proteins for biomanufacturing, synthetic biology, and medicine. We are interested in how a protein’s specific arrangement of amino acids gives rise to complex functions and behaviors, and ways to invert this mapping to design new proteins with tailored properties. The relationships between protein sequence, structure, and function are extraordinarily complex because they involve thousands of molecular interactions that are dynamically coupled across multiple length and time scales. We take a data-driven approach using machine learning and artificial intelligence to decode these relationships at an unprecedented scale. Our research tightly integrates high-throughput and automated experimentation, bioinformatics, large-scale molecular modeling, and machine learning to understand and design protein function.
