Unsupervised Machine Learning for Analysis of Phase Separation in Ternary Lipid Mixture-Reference-Cited by-同舟云学术

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Unsupervised Machine Learning for Analysis of Phase Separation in Ternary Lipid Mixture

Published:2019-09-02 Issue:11 Volume:15 Page:6343-6357
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Löpez Cesar A.^ORCID,Vesselinov Velimir V.,Gnanakaran S.,Alexandrov Boian S.^ORCID

Funder

National Cancer Institute

Los Alamos National Laboratory

Laboratory Directed Research and Development

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.9b00074

Reference82 articles.

1. The in vivo structure of biological membranes and evidence for lipid domains

2. Sphingolipid Organization in the Plasma Membrane and the Mechanisms That Influence It

3. Sizes of lipid domains: What do we know from artificial lipid membranes? What are the possible shared features with membrane rafts in cells?

4. Polyunsaturated Lipids Regulate Membrane Domain Stability by Tuning Membrane Order

5. Partitioning of Thy-1, GM1, and cross-linked phospholipid analogs into lipid rafts reconstituted in supported model membrane monolayers

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