Title
Fast Bayesian Inference for Gene Regulatory Networks Using ScanBMA
Publication Date
4-17-2014
Document Type
Article
Abstract
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.
Publication Title
BMC Systems Biology
Volume
8
Issue
1
DOI
10.1186/1752-0509-8-47
Publisher Policy
open access
Open Access Status
OA Journal
Recommended Citation
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.
https://digitalcommons.tacoma.uw.edu/tech_pub/288
