Simulations meet machine learning in structural biology-Reference-Cited by-同舟云学术

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Simulations meet machine learning in structural biology

Published:2018-04 Issue: Volume:49 Page:139-144
ISSN:0959-440X
Container-title:Current Opinion in Structural Biology
language:en
Short-container-title:Current Opinion in Structural Biology

Author:

Pérez Adrià,Martínez-Rosell Gerard,De Fabritiis Gianni

Funder

Acellera Ltd.

MINECO

Unidad de Excelencia María de Maeztu

European Union's Horizon 2020 research and innovation programme

Publisher

Elsevier BV

Subject

Molecular Biology,Structural Biology

Reference73 articles.

1. Challenges in protein-folding simulations;Freddolino;Nat Phys,2010

2. Are protein force fields getting better? A systematic benchmark on 524 diverse NMR measurements;Beauchamp;J Chem Theory Comput,2012

3. Systematic validation of protein force fields against experimental data;Lindorff-Larsen;PLoS ONE,2012

4. Assessing the accuracy of physical models used in protein-folding simulations: quantitative evidence from long molecular dynamics simulations;Piana;Curr Opin Struct Biol,2014

5. Dynamics of folded proteins;McCammon;Nature,1977

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