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Molecular Insights from Conformational Ensembles via Machine Learning
Biomolecular simulations are intrinsically high dimensional and generate noisy data sets of ever-increasing size. Extracting important features from the data is crucial for understanding the biophysical properties of molecular processes, but remains a big challenge. Machine learning (ML) provides po...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Biophysical Society
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7002924/ https://www.ncbi.nlm.nih.gov/pubmed/31952811 http://dx.doi.org/10.1016/j.bpj.2019.12.016 |