Minimum uncertainty as Bayesian network model selection principle

Minimum uncertainty as Bayesian network model selection principle

Abstract Background Bayesian Network (BN) modeling is a prominent methodology in computational systems biology. However, the incommensurability of datasets frequently encountered in life science domains gives rise to contextual dependence and numerical irregularities in the behavior of model selecti...

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Bibliographic Details
Main Authors: Grigoriy Gogoshin, Andrei S. Rodin
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Bioinformatics
Subjects:
Bayesian networks
Probabilistic networks
Conditional independence
Model selection criteria
Mutual information
Sampling error
Online Access:https://doi.org/10.1186/s12859-025-06104-5
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https://doi.org/10.1186/s12859-025-06104-5

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