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Software . 2023
License: https://www.gnu.org/licenses/gpl-3.0-standalone.html
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Software . 2023
License: https://www.gnu.org/licenses/gpl-3.0-standalone.html
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Molearn v2.0.3: a Python package streamlining the design of generative models of biomolecular dynamics

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 25 Aug 2023 English Publisher:Zenodo
Authors: Musson, Samuel C.; Degiacomi, Matteo T.;

doi: 10.5281/zenodo.8284101 , 10.5281/zenodo.8284102

Molearn v2.0.3: a Python package streamlining the design of generative models of biomolecular dynamics

Abstract

We present molearn, a Python package streamlining the implementation of machine learning models dedicated to the generation of protein conformations from example data obtained via experiment or molecular simulation.

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Keywords

machine learning, molecular dynamics, proteins, Python

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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