BaNDyT: Bayesian Network modeling of molecular Dynamics Trajectories.

ABSTRACT: Bayesian network modeling (BN modeling, or BNM) is an interpretable machine learning method for constructing probabilistic graphical models from the data. In recent years, it has been extensively applied to diverse types of biomedical datasets. Concurrently, our ability to perform long-timescale molecular dynamics (MD) simulations on proteins and other materials has increased exponentially. However, the analysis of MD simulation trajectories has not been data-driven but rather dependent on the user's prior knowledge of the systems, thus limiting the scope and utility of the MD simulations. Recently, we pioneered using BNM for analyzing the MD trajectories of protein complexes. The resulting BN models yield novel fully data-driven insights into the functional importance of the amino acid re

SUBMITTER: Mukhaleva E 

PROVIDER: S-EPMC11581029 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature