Machine Learning-Driven Protein Design and Engineering
Our Research
Proteins are amazingly diverse molecules that are capable of performing complex chemical and biological functions. Such versatility presents tremendous opportunities for solving challenging human problems that range from medicine and agriculture to environmental protection and industrial chemistry. Our ability to design proteins with tailor-made functions has been impeded by our limited understanding of these complex molecules. The Romero Lab studies the design principles of proteins and how they can be applied to engineer new molecular functions. We believe technological advances in both computational and experimental methods will drive our understanding of the relationships between protein sequence, structure, and function. Therefore, a large part of our work focuses on developing new methods to probe these relationships on an unprecedented scale. These methods leverage advances in DNA sequencing/synthesis, microfluidics, molecular modeling, machine learning, and optimization.
NAVIGATION OF PROTEIN FITNESS LANDSCAPES
SELF-DRIVING LABS FOR BIOLOGY
PROTEIN ENGINEERING FOR THERAPEUTICS
PROTEIN ENGINEERING FOR BIOCATALYSIS AND METABOLIC ENGINEERING
RECENT LAB NEWS
NISHIT SUCCESSFULY DEFENDS THESIS
Congratulations to our own Nishit for defending his thesis entitled “High-throughput screening and ML-aided engineering of transcription factor based biosensors
CHASE’S PAPER PUBLISHED IN NATURE COMMS
Congratulations to Chase, Sarah, and Pete for their work entitled “Neural network extrapolation to distant regions of the protein fitness landscape” in Nature Comms!
LAB MOVING TO DUKE UNIVERSITY IN AUGUST
The Romero lab is officially moving to Duke in early August. We are super excited to begin a new journey in Durham!