Exploring soybean metabolic pathways based on probabilistic graphical model and knowledge-based methods

Jie Hou, Gary Stacey, Jianlin Cheng
2015 EURASIP Journal on Bioinformatics and Systems Biology  
Soybean (Glycine max) is a major source of vegetable oil and protein for both animal and human consumption. The completion of soybean genome sequence led to a number of transcriptomic studies (RNA-seq), which provide a resource for gene discovery and functional analysis. Several data-driven (e.g., based on gene expression data) and knowledge-based (e.g., predictions of molecular interactions) methods have been proposed and implemented. In order to better understand gene relationships and
more » ... interactions, we applied probabilistic graphical methods, based on Bayesian network and knowledgebase constraints using gene expression data to reconstruct soybean metabolic pathways. The results show that this method can predict new relationships between genes, improving on traditional reference pathway maps.
doi:10.1186/s13637-015-0026-5 pmid:28194174 pmcid:PMC5270328 fatcat:z47anngrk5ewtlygzsmmek6jba