Rana A. Barghout
PhD
Co-advised with Krishna Mahadevan
Publications within the group (2)
kinGEMs: A scalable framework for resource-constrained models through stochastic tuning of deep learning-predicted kinetic parameters / PLOS Comput Biol / '26
Couples deep learning turnover number predictions with stochastic simulated annealing to parameterize enzyme-constrained genome-scale models across 93 organisms, resolving long-standing biocatalytic data sparsity.
Graph Data Modeling: Molecules, Proteins, & Chemical Processes / ACS In Focus / '25
A foundational pedagogical text and monograph introducing structural, geometric, and kinetic graph neural networks for molecules, macromolecular proteins, and complex biological pathways.
José Manuel Barraza-Chavez, Rana A. Barghout, Ricardo Almada-Monter, Adrian Jinich, Radhakrishnan Mahadevan, Benjamin Sanchez-Lengeling