Work

Editorial: Machine Learning in Biomolecular Simulations

Year: 2019

Type: editorial

Abstract: "Interest in machine learning is growing in all fields of science, industry, and business. This interest was not primarily initiated by new theoretical findings. Interestingly, the theoretical basis of the majority of machine learning techniques, such as artificial neural networks, decision trees, or kernel methods, have been known for a relatively long time. Instead, there are other effects that triggered the recent boom of machine learning."

Source: Frontiers in Molecular Biosciences

DOI: 10.3389/fmolb.2019.00076

Authors: Gennady Verkhivker, Vojtech Spiwok, Francesco Luigi Gervasio

Institutions: Chapman University, University of Chemistry and Technology, Prague, University College London

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,490

OpenAlex ID: W2968756798

Cites:

Cited by: 5

Related to: 10