Molecular Simulation, Volume 44, Issue 11 (2018)

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Molecular Simulation, Volume 44, Issue 11 (2018)

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Machine Learning

Editorial

Editorial
Machine learning
Jerome Delhommelle
Page: 865
Published online: 23 May 2018
CitationforMachine learning | Full Text | PDF (230.6 KB)
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Articles

Article
Understanding the thermal properties of amorphous solids using machine-learning-based interatomic potentials
Gabriele C. Sosso, Volker L. Deringer, Stephen R. Elliott & Gábor Csányi
Pages: 866-880
Published online: 13 Mar 2018
AbstractforUnderstanding the thermal properties of amorphous solids using machine-learning-based interatomic potentials | Full Text | References | PDF (4.1 MB)
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Article
Towards the simulation of biomolecules: optimisation of peptide-capped glycine using FFLUX
Joseph C. R. Thacker, Alex L. Wilson, Zak E. Hughes, Matthew J. Burn, Peter I. Maxwell & Paul L. A. Popelier
Pages: 881-890
Published online: 11 Feb 2018
AbstractforTowards the simulation of biomolecules: optimisation of peptide-capped glycine using FFLUX | Full Text | References | PDF (1.3 MB) | Supplemental
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Article
Recruiting machine learning methods for molecular simulations of proteins
Shriyaa Mittal & Diwakar Shukla
Pages: 891-904
Published online: 13 Mar 2018
AbstractforRecruiting machine learning methods for molecular simulations of proteins | Full Text | References | PDF (2.9 MB)
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Article
Representing molecular and materials data for unsupervised machine learning
E. Swann, B. Sun, D. M. Cleland & A. S. Barnard
Pages: 905-920
Published online: 02 Apr 2018
AbstractforRepresenting molecular and materials data for unsupervised machine learning | Full Text | References | PDF (3.7 MB)
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Article
Building and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space
Johannes Hachmann, Mohammad Atif Faiz Afzal, Mojtaba Haghighatlari & Yudhajit Pal
Pages: 921-929
Published online: 22 May 2018
AbstractforBuilding and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space | Full Text | References | PDF (3 MB)
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Article
Machine learning and molecular design of self-assembling -conjugated oligopeptides
Bryce A. Thurston & Andrew L. Ferguson
Pages: 930-945
Published online: 09 May 2018
AbstractforMachine learning and molecular design of self-assembling -conjugated oligopeptides | Full Text | References | PDF (2.9 MB)
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