biostudies-literatureLatham APMEXT | Japan Society for the Promotion of ScienceDeutsche Forschungsgemeinschaft (DFG)MEXT | Japan Society for the Promotion of Science (JSPS)Deutsche ForschungsgemeinschaftHHS | NIH | National Institute of General Medical SciencesEuropean Molecular Biology Laboratory Interdisciplinary Postdoc ProgrammeEuropean Molecular Biology LaboratoryBaden-Württemberg StiftungBaden-Württemberg Stiftung (BWS)HHS | NIH | National Institute of General Medical Sciences (NIGMS)NIGMS NIH HHSEuropean Molecular Biology Laboratory (EMBL)e2415674122https://www.ebi.ac.uk/biostudies/studies/S-EPMC11929490biostudies-literatureUnknown122(11)Dynamic processes involving biomolecules are essential for the function of the cell. Here, we introduce an integrative method for computing models of these processes based on multiple heterogeneous sources of information, including time-resolved experimental data and physical models of dynamic processes. First, for each time point, a set of coarse models of compositional and structural heterogeneity is computed (heterogeneity models). Second, for each heterogeneity model, a set of static integrative structure models is computed (a snapshot model). Finally, these snapshot models are selected and connected into a series of trajectories that optimize the likelihood of both the snapshot models and transitions between them (a trajectory model). The method is demonstrated by application to the aProceedings of the National Academy of Sciences of the United States of AmericaIntegrative spatiotemporal modeling of biomolecular processes: Application to the assembly of the nuclear pore complex.PMC11929490N/AProject-ID 511488495 - SFB 1638 P06P41GM109824R01GM083960F32GM150243R01GM112108F32 GM150243Zhang WEllenberg JSali ATempkin JOBLatham APOtsuka SfalseIntegrative spatiotemporal modeling of biomolecular processes: Application to the assembly of the nuclear pore complex.Dynamic processes involving biomolecules are essential for the function of the cell. Here, we introduce an integrative method for computing models of these processes based on multiple heterogeneous sources of information, including time-resolved experimental data and physical models of dynamic processes. First, for each time point, a set of coarse models of compositional and structural heterogeneity is computed (heterogeneity models). Second, for each heterogeneity model, a set of static integrative structure models is computed (a snapshot model). Finally, these snapshot models are selected and connected into a series of trajectories that optimize the likelihood of both the snapshot models and transitions between them (a trajectory model). The method is demonstrated by application to the a2025-01-01T00:00:00Z2025 Mar2026-04-08T19:54:21.828Z2025-07-06T03:04:27.949ZS-EPMC119294904008565310.1073/pnas.2415674122