Published September 23, 2020
| Version v1
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Predicting Hydrophobicity by Learning Spatiotemporal Features of Interfacial Water Structure: Combining Molecular Dynamics Simulations with Convolutional Neural Networks
Description
Files for reproducing results from Kelkar et al. (JPCB 2020) - Predicting Hydrophobicity by Learning Spatiotemporal Features of Interfacial Water Structure: Combining Molecular Dynamics Simulations with Convolutional Neural Networks
This folder contains simulations starter files and also plug-and-play datasets to test ML algorithms on molecular dynamics (MD) simulation data.
All analysis scripts can also be found on GitLab on this link: https://gitlab.com/atharva-kelkar/kelkar_et_al_jpcb_2020
Files
Files
(16.4 GB)
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md5:1795d75d767327bbe3085d6b9fe15af9
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16.4 GB | Download |
md5:ca19c55f3c524ad491fb1e01827e3c42
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18.1 kB | Download |