Fast Bayesian Inference for Gene Regulatory Networks Using ScanBMA
Genome-wide time-series data provide a rich set of information for discovering gene regulatory relationships. As genome-wide data for mammalian systems are being generated, it is critical to develop network inference methods that can handle tens of thousands of genes efficiently, provide a systematic framework for the integration of multiple data sources, and yield robust, accurate and compact gene-to-gene relationships.
BMC Systems Biology
Young, William Chad; Raftery, Adrian E.; and Yeung, Ka Yee, "Fast Bayesian Inference for Gene Regulatory Networks Using ScanBMA" (2014). School of Engineering and Technology Publications. 288.