Article

Molecular insights from conformational ensembles via machine learning

2019-07-07

Abstract excerpt

<h4>ABSTRACT</h4> Biomolecular simulations are intrinsically high dimensional and generate noisy datasets of ever increasing size. Extracting important features in the data is crucial for understanding the biophysical properties of molecular processes, but remains a big challenge. Machine learning (ML) provides powerful dimensionality reduction tools. However, such methods are often criticized to resemble black b...

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Literature Corpus work: b47c6dae-eb4f-53f9-a42d-e37168aafe5b
DOI: 10.1101/695254

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