2009 Poster Sessions : Computational Prediction of Vertebrate Enhancer Elements

Student Name : Aaron Wenger
Advisor : Gill Bejerano
Sequencing of the human and mouse genomes revealed that while 5% of the genome is subject to purifying selection - and hence likely functional - only 1.5% codes for proteins. Much of the remaining conserved portion presumably consists of the "control" that activates and represses gene expression in a time and tissue-specific manner.
Activating elements are termed "enhancers" and repressing elements are termed "silencers." These enhancers and silencers are dispersed across large regions of the genome and are difficult to differentiate from the mass on DNA in which they lie. Experimental assays for identifying enhancers and silencers are time-consuming and limited. We have developed a computational approach to identify enhancers as conserved clusters of transcription factor binding sites and have applied our tools to predict experimentally verified enhancers.

Aaron Wenger is a graduate student in Computer Science working in the lab of Gill Bejerano. He grew up in Pennsylvania and studied Computer Engineering at the University of Notre Dame. Following college, Aaron worked as an IT consultant for two years before coming to Stanford to study computational biology.