Transcription analysis with gene expression and network connectivity data

BIOT 179

Mark P. Brynildsen, mbrynild@ucla.edu1, Linh M. Tran1, Tung-Yun Wu, d937604@oz.nthu.edu.tw2, Shi-Shang Jang2, and James C. Liao1. (1) Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, 420 Westwood Plaza, 5806 Boelter Hall, Los Angeles, CA 90025, (2) Department of Chemical Engineering, National Tsing-Hua University, Hsinchu 30043, Taiwan
DNA microarray and ChIP-chip binding assays are technologies that provide complimentary, genome-wide measurements of transcriptional regulation. These data sources have been used individually and in conjunction to define key features of transcription regulation, namely the transcription network and transcription factor activities. This is due to the difficulty associated with measuring these features directly. Reliance on DNA microarray and ChIP-chip binding data to determine the transcriptional response to external and internal stimuli has become commonplace. However, we have shown that noise and environment-specific transcription network variation can significantly impact transcription analyses. The extent of this impact can be drastic, sometimes resulting in ChIP-chip derived networks performing as well as random networks. Here we present two methods aimed at mitigating the adverse impact with which noise and transcription network variation affect the ability of transcription analyses to deduce transcription networks and transcription factor activities.
 

Emerging Technologies: Systems Biology
8:00 AM-11:00 AM, Wednesday, August 22, 2007 BCEC -- 108, Oral

Division of Biochemical Technology

The 234th ACS National Meeting, Boston, MA, August 19-23, 2007