Toward Predictive Biology: Bridging Mechanistic and Data-Driven Models

Abstract:  

Systems biology seeks to predict and design complex biological behaviors by integrating experimental data, computation, and mechanistic understanding. This talk explores the “sweet spot” between first-principles modeling and data-driven approaches, highlighting how each offers complementary strengths for understanding biological systems. Through examples spanning plant stress responses, microbial and host metabolism, enzyme kinetics, and cancer, the talk demonstrates how genome-scale metabolic models, machine learning, and hybrid frameworks can uncover biological mechanisms and generate predictive insights. Ultimately, integrating mechanistic knowledge with data-driven learning provides a powerful path toward interpretable, context-aware models and, eventually, biological digital twins.

Bio:

Rajib Saha is the Richard L. and Carol S. McNeel associate professor and the chair of the graduate program of the Department of Chemical Engineering at University of Nebraska-Lincoln. He got his BS in Chemical Engineering from Bangladesh University of Engineering & Technology and MS and PhD from the Department of Chemical Engineering at Penn State and did his postdoctoral training at the Department of Biology at Washington University in St. Louis. Currently, he leads the Systems and Synthetic Biology Laboratory at UNL that focuses on studying non-model microbes, microbial communities, plants, and human diseases. His research work is funded by NIH, NSF, USDA, AFOSR, ARO, Nebraska Corn Board, and Nebraska Ethanol Board. He has been awarded NIH Outstanding Early Career Investigator Award (MIRA) and NSF CAREER grant. He is also the recipient of 2026 UNL College of Engineering Distinguished Research Award, 2024 UNL Dean’s Graduate Mentoring Award, 2022 UNL College of Engineering Edgerton Innovation Award, and 2020 Penn State Early Career Alumni Recognition Award.