Bayesian networks: a powerful tool for systems biology study

摘要

The wide application of omics research approaches caused a burst of biological data in the past decade,and also promoted the growth of systems biology,a research field that studies biological questions from a genome-wide point of view.One feature of systems biology study is to integrate and identify.Not only experiments are carried out at whole-genome scales,but also data from various resources,such as genomics,transcriptomics,proteomics,and metabolics data,need to be integrated to identify correlations among targeted entities.Therefore,plenty amounts of experimental data,robust statistical methods,and reliable network construction models are indispensable for systems biology study.Among the available network construction models,Bayesian network is considered as one of the most effective methods available so far for biological network predictions(Pe’er,2005).