BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories

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 data sets. Concurrently, our ability to perform long-time scale m...

Full description

Saved in:
Bibliographic Details
Main Author: Elizaveta Mukhaleva (20602550) (author)
Other Authors: Babgen Manookian (8805551) (author), Hanyu Chen (2735152) (author), Indira R. Sivaraj (20602553) (author), Ning Ma (155058) (author), Wenyuan Wei (8044832) (author), Konstancja Urbaniak (20602556) (author), Grigoriy Gogoshin (8988647) (author), Supriyo Bhattacharya (1313307) (author), Nagarajan Vaidehi (333668) (author), Andrei S. Rodin (8988653) (author), Sergio Branciamore (8180826) (author)
Published: 2025
Subjects:
Biophysics
Biochemistry
Genetics
Biological Sciences not elsewhere classified
Chemical Sciences not elsewhere classified
Information Systems not elsewhere classified
comprehensive python interface
amino acid residues
bayesian network modeling
pioneered using bnm
first software package
biomedical data sets
md simulation trajectories
bnm specifically attuned
bandyt software package
analyzing md trajectories
md trajectories
bn modeling
software ’
associated software
versatile mechanism
user ’
thus limiting
selectively couple
recent years
rather dependent
prior knowledge
perform long
methods associated
increased exponentially
include specialized
functional importance
extensively applied
diverse types
coupled receptors
application example
advanced features
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items