Bayesian learning boosts gene research accuracy
Researchers at The University of Texas at Arlington have developed a new computational tool that helps scientists pinpoint proteins known as transcriptional regulators that control how genes turn on and off. In a study recently published in the peer-reviewed journal Nature Communications, Dr. Wang and her colleagues—Zeyu Lu, a postdoctoral researcher in her lab at UTA, and Lin Xu, a researcher at UT Southwestern Medical School—introduce a tool called Bayesian Identification of Transcriptional Regulators from Epigenomics-Based Query Regions Sets, or BIT.
