The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Multiscale modeling of emergent materials: biological and soft matter
Open accessAbstract
In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed in the context of the so-called Henderson theorem and the inverse Monte Carlo method of Lyubartsev and Laaksonen. In the second part, we take a different look at coarse graining by analyzing conformations of molecules. This is done by the application of self-organizing maps, i.e., a neural network type approach. Such an approach can be used to guide the selection of the relevant degrees of freedom. Then, we discuss technical issues related to the popular dissipative particle dynamics (DPD) method. Importantly, the potentials derived using the inverse Monte Carlo method can be used together with the DPD thermostat. In the final part we focus on solvent-free modeling which offers a different route to coarse graining by integrating out the degrees of freedom associated with solvent.
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Cites
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Cited by
Perspective: Coarse-grained models for biomolecular systems
Noid, W. G. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4818908 · Cited by 893
Versatile object-oriented toolkit for coarse-graining applications
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Classical Electrostatics for Biomolecular Simulations
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Self-citationWho is left out: exploring social boundaries in entrepreneurial ecosystems
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Metadata
- Authors
- Murtola, T., Bunker, A., Vattulainen, I., Deserno, M., & Karttunen, M.
- Venue
- Physical Chemistry Chemical Physics
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2009
- Volume
- 11
- Issue
- 12
- Pages
- 1869
- ISSN
- 1463-9076 (ISSN-L)
- 1463-9084
- OpenAlex
- W1979853160
- Cited by
- 264
- References
- 9
- FWCI
- 14.20
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
