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From bioinformatics, to the automatic construction of collective variables to describe rare events, machine learning has been part of biomolecular modeling for a longer time than in other fields of chemical physics.
ML techniques are exceptionally useful in solving a wide variety of problems related to analysis of complex MD simulation data, such as to discover reaction ...
Jul 25, 2023 · Routine access to high-quality electronic structure calculations is a tantalizing prospect that would be highly valued across subfields of ...
Jan 19, 2024 · Biomedical engineers at Duke University have developed a new method to improve the effectiveness of machine learning models.
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Aug 15, 2023 · By training models to represent the biomolecular world, we create a digital version of these hidden systems that are controllable and malleable, ...
Dec 27, 2022 · ML and MM methods offer quite complementary approaches for molecular modeling. As such, there are a growing number of studies that aim at ...
Missing: biomolecular | Show results with:biomolecular
From bioinformatics, to the automatic construction of collective variables to describe rare events, machine learning has been part of biomolecular modeling for ...
Missing: modelling. | Show results with:modelling.
Jun 4, 2019 · Machine learning (ML) has become a crucial component of early drug discovery. This research area has been fueled by two main factors.
This Research Topic collection will focus on the application of machine learning algorithms in biomolecular simulations. In particular, it will cover the ...
Machine learning has been proposed as an alternative to theoretical modeling when dealing with complex problems in biological physics.