biostudies-literatureRaveh BNIAID NIH HHSNIHNIGMS NIH HHSe2104559118https://www.ebi.ac.uk/biostudies/studies/S-EPMC8536362biostudies-literatureUnknown118(35)Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide and conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each input model can in principle be based on any type of data and can describe a different aspect of the modeled system using any mathematical representation, scale, and level of granularity. These input models are 1) converted to a standardized statistical representation relying on probabilistic graphical models, 2) coupled by modeling their mutual relations with the physical world, and 3) finally harmonized with respect to each other. To illustrate Bayesian metamodeling, we proProceedings of the National Academy of Sciences of the United States of AmericaBayesian metamodeling of complex biological systems across varying representations.PMC8536362U19AI135990R01 GM083960P41GM109824R01GM083960U19 AI135990P41 GM109824Tempkin JWang CSali AGraham NASingla JSun LSanyal TKesselman CWhite KLBharath KLi AZhao JStevens RCRaveh BZheng DfalseBayesian metamodeling of complex biological systems across varying representations.Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide and conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each input model can in principle be based on any type of data and can describe a different aspect of the modeled system using any mathematical representation, scale, and level of granularity. These input models are 1) converted to a standardized statistical representation relying on probabilistic graphical models, 2) coupled by modeling their mutual relations with the physical world, and 3) finally harmonized with respect to each other. To illustrate Bayesian metamodeling, we pro2021-01-01T00:00:00Z2021 Aug2026-07-16T14:33:03.625Z2025-04-05T14:05:19.236ZS-EPMC85363623445300010.1073/pnas.2104559118