Simple Bayesian Gene Network Learning in Populus Drought Transcriptome Data

Amir Almasi Zadeh Yaghuti, Ali Movahedi, Hui Wei, Weibo Sun, Mohaddeseh Mousavi, Qiang Zhuge
2021 Bangladesh Journal of Botany  
Constructing a sensibly functional gene interaction network is highly appealing for better understanding system-level biological processes governing various Populus traits. Bayesian Network (BN) learning provides an elegant and compact statistical approach for modeling causal gene-gene relationships in microarray data. Therefore, it could come with the illumination of functional molecular playing in Biology Systems. In the present study, different forms of gene Bayesian networks were detected
more » ... Populus cellular transcriptome data. Markov blankets would likely be emerging at every possible gene regulatory Bayesian network level. Results showed that PtpAffx.1257.4.S1_a_at,1.0 hypothetical protein is the most important in its possible regulatory program. This paper illustrates that the gene network regulatory inference is possible to encapsulate within a single BN model. Therefore, such a BN model can serve as a promising training tool for Populus gene expression data for better future experimental scenarios. Bangladesh J. Bot. 50(4): 1077-1086, 2021 (December)
doi:10.3329/bjb.v50i4.57075 fatcat:isbgnb2n4rhrdipvne5ruo3meq