biostudies-literatureTourigny DSLife Sciences Research FoundationNational Institutes of HealthNIGMS NIH HHSNational Science Foundation5231-5242https://www.ebi.ac.uk/biostudies/studies/S-EPMC8715178biostudies-literatureUnknown120(23)Stochasticity from gene expression in single cells is known to drive metabolic heterogeneity at the level of cellular populations, which is understood to have important consequences for issues such as microbial drug tolerance and treatment of human diseases like cancer. Despite considerable advancements in profiling the genomes, transcriptomes, and proteomes of single cells, it remains difficult to experimentally characterize their metabolism at the genome scale. Computational methods could bridge this gap toward a systems understanding of single-cell biology. To address this challenge, we developed stochastic simulation algorithm with flux-balance analysis embedded (SSA-FBA), a computational framework for simulating the stochastic dynamics of the metabolism of individual cells using genomBiophysical journalSimulating single-cell metabolism using a stochastic flux-balance analysis algorithm.PMC87151781649014R35GM119771R35 GM119771Karr JRTourigny DSGoldberg APfalseSimulating single-cell metabolism using a stochastic flux-balance analysis algorithm.Stochasticity from gene expression in single cells is known to drive metabolic heterogeneity at the level of cellular populations, which is understood to have important consequences for issues such as microbial drug tolerance and treatment of human diseases like cancer. Despite considerable advancements in profiling the genomes, transcriptomes, and proteomes of single cells, it remains difficult to experimentally characterize their metabolism at the genome scale. Computational methods could bridge this gap toward a systems understanding of single-cell biology. To address this challenge, we developed stochastic simulation algorithm with flux-balance analysis embedded (SSA-FBA), a computational framework for simulating the stochastic dynamics of the metabolism of individual cells using genom2021-01-01T00:00:00Z2021 Dec2025-04-04T23:44:43.975Z2025-04-04T23:44:43.975ZS-EPMC87151783475707610.1016/j.bpj.2021.10.038