About the group
Our work focuses on using computer simulations, global optimization, and machine learning to model biology across the molecular and systems scales, and then leveraging these models for therapeutic design. To tackle these challenges, we develop mechanistic and data-driven models that can predict how molecular changes affect therapeutic properties, as well as, how these properties relate to drug efficacy at cellular, tissue, or organismal scales. To support our therapeutic design research, our work also includes general advancements in machine learning and optimization algorithms. On this site you will find descriptions of current and past projects, along with relevant publications. You will also find details of our efforts to develop computational resources for education, and please feel free to reach out if you have any questions.
Highlights
Our Research
Our research has two main focuses, Data-driven Therapeutic Design and Multi-scale Biomolecular Modeling, and integrates molecular and systems modeling with machine learning and optimization.
Published Work
Our published work includes comptuational tool development for machine learning and optimization, as well as, application specific models in the areas of Immunology, Cancer Biology, and Computational Drug Design. (Painting by David S. Goodsell)
Tool Development
We are developing open source tools for research and education at the intersection of molecular/systems modeling, machine learning and optimization.
Our Team
Our team is highly collaborative and strives to find creative solutions to challenging problems in therapeutic design.