Computing for Biology & Health
Rice University sits minutes from the Texas Medical Center, the world's largest medical complex, with more than 60 institutions and 106,000 employees. That proximity is not background. It shapes what our faculty work on, who they collaborate with and what clinical translation actually looks like.
Research in this area spans biological and health systems at every scale: from individual nucleotides, genes and proteins up through molecular networks, tissues and entire populations. Our faculty develop and apply computational methods to understand complex biological processes and to address real clinical challenges.
- The Kavraki Lab works at the intersection of robotics, computational biomedicine and physical AI, producing open-source tools including the Open Motion Planning Library (OMPL) used in research labs worldwide.
- The Treangen Lab develops scalable algorithms for identifying and characterizing microbial pathogens, studying genome variation at the population scale and analyzing environmental microbiomes, funded by CDC, NIH and NSF.
- The ylaboratory focuses on decoding disease with data, building computational methods for neurological disease, cancer and chronic illness from genomic and clinical datasets.
- Current projects also include vision-language foundation models for radiology, protein structure prediction, and molecular interaction and signaling network analysis.
Applications reach across cancer, neurodegenerative disease, cardiac and infectious conditions, precision health and biosecurity.
“The Texas Medical Center is not just nearby. It is part of how we think about what computing should do.”
What We Explore
- How does a model predict a protein's 3D structure from its amino acid sequence?
- What can genomic data reveal about disease mechanisms, and how do you compute that at the population scale?
- How do vision-language models interpret a radiology image, and where do they differ from a clinician?
- What computational tools can identify biosecurity threats from microbial sequence data?
- How do you model how a therapeutic will interact with a disease across a diverse population?
Faculty
Faculty members leading research in Computing for Biology & Health are as follows:
- Luay Nakhleh William and Stephanie Sick Dean, GRB School of Engineering and Computing; Guggenheim Fellow; Sloan Fellow; ISCB Fellow; AAAS Fellow
- Todd Treangen NSF CAREER Award (2023); Treangen Lab - Bioinformatics & Computational Biology, funded by CDC, NIH, NSF
- Lydia Kavraki Kenneth and Audrey Kennedy Professor of Computing; NAE; NAM; NAS; AAAS; ACM Fellow; IEEE Fellow; IEEE Frances E. Allen Medal 2023; Allen Newell Award 2019; Kavraki Lab - Physical AI, Robotics & Biomedicine
- Vicky Yao NSF CAREER Award (2022); ylaboratory - Decoding Disease with Data