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How to learn from inconsistencies: Integrating molecular simulations with experimental data

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningfagfællebedømt

Molecular simulations and biophysical experiments can be used to provide independent and complementary insights into the molecular origin of biological processes. A particularly useful strategy is to use molecular simulations as a modeling tool to interpret experimental measurements, and to use experimental data to refine our biophysical models. Thus, explicit integration and synergy between molecular simulations and experiments is fundamental for furthering our understanding of biological processes. This is especially true in the case where discrepancies between measured and simulated observables emerge. In this chapter, we provide an overview of some of the core ideas behind methods that were developed to improve the consistency between experimental information and numerical predictions. We distinguish between situations where experiments are used to refine our understanding and models of specific systems, and situations where experiments are used more generally to refine transferable models. We discuss different philosophies and attempt to unify them in a single framework. Until now, such integration between experiments and simulations have mostly been applied to equilibrium data, and we discuss more recent developments aimed to analyze time-dependent or time-resolved data.

OriginalsprogEngelsk
TitelComputational Approaches for Understanding Dynamical Systems : Protein Folding and Assembly
RedaktørerBirgit Strodel, Bogdan Barz
Antal sider54
ForlagAcademic Press
Publikationsdato2020
Sider123-176
Kapitel3
ISBN (Trykt)978-0-12-821135-9
DOI
StatusUdgivet - 2020
NavnProgress in Molecular Biology and Translational Science
Vol/bind170
ISSN1877-1173

ID: 237999356