Dataset - Multi-omics-driven kinetic modeling reveals metabolic vulnerabilities and differential drug-response dynamics in ovarian cancer

Dataset required to reproduce the simulation runs from the study "Multi-omics-driven kinetic modeling reveals metabolic vulnerabilities and differential drug-response dynamics in ovarian cancer" by Toumpe et al. The accompanying code is available at: https://github.com/EPFL-LCSB/human-cancer-kinetic-models Dataset contains: Steady-state samples for both physiologies, used to represent the metabolic flux and metabolite concentration distributions for parametrizing the kinetic models. Kinetic parameter sets for the BRCA1_wt and BRCA1_mut physiologies, which were used to compute the distributions of control coefficients. Representative kinetic parameter sets for both physiologies, selected from the larger ensembles, which can be used to reproduce the case-study simulations, explore dynamic responses, and perform additional hypothesis-testing analyses. The second part of the dataset can be found at https://zenodo.org/records/17349420.