Bayesian network feature finder (BANFF): an R package for gene network feature selection | Zendy

Zhou Lan | Zendy; Yize Zhao | Zendy; Jian Kang | Zendy; Tianwei Yu | Zendy

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Bayesian network feature finder (BANFF): an R package for gene network feature selection

Author(s) -

Zhou Lan,

Yize Zhao,

Jian Kang,

Tianwei Yu

Publication year - 2016

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btw522

Subject(s) - computer science , markov chain monte carlo , feature selection , inference , feature (linguistics) , graphical model , data mining , bayesian network , r package , bayesian inference , artificial intelligence , machine learning , model selection , bayesian probability , philosophy , linguistics , computational science

Network marker selection on genome-scale networks plays an important role in the understanding of biological mechanisms and disease pathologies. Recently, a Bayesian nonparametric mixture model has been developed and successfully applied for selecting genes and gene sub-networks. Hence, extending this method to a unified approach for network-based feature selection on general large-scale networks and creating an easy-to-use software package is on demand.

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