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Protein Science
Article . 2025
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Tutorial on integrative spatiotemporal modeling by integrative modeling platform

Authors: Andrew P. Latham; Miha Rožič; Benjamin M. Webb; Andrej Sali;

Tutorial on integrative spatiotemporal modeling by integrative modeling platform

Abstract

AbstractCells function through dynamic interactions between macromolecules. Detailed characterization of the dynamics of large biomolecular systems is often not feasible by individual biophysical methods. In such cases, it may be possible to compute useful models by integrating multiple sources of information. We have previously developed an integrative method to model dynamic processes by computing biomolecular heterogeneity at fixed time points, then generating static integrative structural modes for each of these heterogeneity models, and finally connecting these static models to produce a scored trajectory model that depicts the process. Here, we demonstrate how to compute, score, and assess these integrative spatiotemporal models using our open‐source Integrative Modeling Platform (IMP) program (https://integrativemodeling.org/).

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United States
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Keywords

integrative structure modeling, Models, Molecular, Tools for Protein Science, Bioinformatics and Computational Biology, Biophysics, Molecular, Bioengineering, Computation Theory and Mathematics, Biological Sciences, biomolecular processes, molecular dynamics, Models, Biochemistry and cell biology, Medicinal and biomolecular chemistry, structural biology, Biochemistry and Cell Biology, Other Information and Computing Sciences, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average