We seek to understand complex biological processes and inform the development of new drugs and proteins based on computer models of biomolecules’ structure and dynamics. Major foci include using simulations to understand proteins’ moving parts and using deep learning to design new proteins and drugs.
Researchers
How are biological structures formed and maintained? How do they manifest biological function? These are central questions in biology that date back thousands of years, to the time of Aristotle. We address the same fundamental questions at a molecular level: how is the diverse and beautiful array of protein and nucleic acid structures formed, and how do they carry out their biological function? Our research addresses these questions using the tools and principles of biophysics, including thermodynamics, statistical mechanics, simulations, and computational geometry.
Computational Biology Computational Biology
The Bowman lab takes a physics-based approach to precision medicine, devising new ways to develop therapeutics and interpret genetic variation by understanding/exploiting protein dynamics. They achieve this using a combination of biophysical experiments, machine learning, physics-based simulations, and the world’s largest distributed computer.
Computational Biology Computational Biology
The Kulp Laboratory seeks to inspire innovative solutions to long standing problems in the development of efficacious vaccines through the fusion of artificial intelligence and protein structure engineering. New cutting-edge protein design and structure determination methods allow for exciting, rapid and iterative vaccine science. The lab focuses on creating immunogens for diseases that impose a significant health impact and without broadly effective vaccines, such as HIV, SARS-CoV-2, Influenza and Lassa, among others. Biophysical techniques, novel transgenic animal models, and advanced structural assessments are employed to study immune responses of next-generation vaccines. The lab posits that computational approaches can now be used to tackle previously insurmountable challenges ushering in a new era of precision structural vaccinology.
Computational Biology Computational Biology cryoEM
Our research interests lie at the interface of chemical physics and molecular biology. Our goal is to provide molecular level characterization of complex biomolecular systems and formulate quantitatively accurate microscopic models for predicting the interactions of various therapeutic agents with innate biochemical signaling mechanisms. We employ several computational algorithms ranging from techniques to treat electronic structure, molecular dynamics, Monte Carlo simulations, stochastic kinetic equations, and complex systems analyses in conjunction with the theoretical formalisms of statistical and quantum mechanics, and high performance computing in massively parallel architectures.
Computational Biology Computational Biology