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Analyzing Biomolecular Ensembles
Lambrughi, M. ✉
;
Tiberti, M. ✉
;
Allega, M.F. ✉
;
Sora, V.
;
Nygaard, M. ✉
;
Toth, A. [Tóth, Ágota (biofizika), author]
;
Salamanca, Viloria J.
;
Bignon, E.
;
Papaleo, E. ✉
English Chapter (Chapter in Book) Scientific
Published:
Bonomi Massimiliano et al. Biomolecular Simulations: Methods and Protocols. (2019) ISBN:9781493996070; 9781493996087; 9781493996100
pp. 415-451
Identifiers
MTMT: 30858557
DOI:
10.1007/978-1-4939-9608-7_18
WoS:
000520549800020
Scopus:
85071281060
Several techniques are available to generate conformational ensembles of proteins and other biomolecules either experimentally or computationally. These methods produce a large amount of data that need to be analyzed to identify structure–dynamics–function relationship. In this chapter, we will cover different tools to unveil the information hidden in conformational ensemble data and to guide toward the rationalization of the data. We included routinely used approaches such as dimensionality reduction, as well as new methods inspired by high-order statistics and graph theory. © Springer Science+Business Media, LLC, part of Springer Nature 2019.
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2025-04-25 05:00
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