Technologies for making genome-wide observations

The increasing rate of high-confidence computational predictions has rapidly overwhelmed our ability to validate them using traditional experimental methods.  This inadequacy is perhaps felt most strongly in the field of transcriptional network analysis where hundreds of high quality predictions await their turn in a lengthy queue with often slow and laborious rate-limiting steps.  Our ability to make rapid progress in mapping regulatory networks and understanding their dynamics depends on inexpensive, high-throughput technologies for validating computational predictions.  In turn, progress on the computational side relies on rapid feedback from validation studies that quickly establish the sensitivity and accuracy of predictions.  In order to address this bottle-neck in the field of cis-regulatory motif identification, we are developing a variety of high-throughput genetic and biochemical technologies to rapidly identify transcription factors that bind our computationally predicted cis-regulatory elements.  Another limitation of modern approaches for modeling transcriptional network dynamics is the lack of systematic in vivo observations of the molecular events that orchestrate changes in gene expression.  To address this challenge, we are developing technologies that allows us to quantitatively monitor the in vivo occupancy of most (possibly all) proteins on DNA.

Selated publications:

Global discovery of adaptive mutations
Nature Methods. 2009 Aug; 6(8):581-3
Goodarzi H., Hottes, AK., Tavazoie S.

Global protein occupancy landscape of a bacterial genome
Molecular Cell. 2009 Jul 31;35(2):247-53
Vora T., Hottes, AK., Tavazoie S.

Microarray profiling of phage-display selections for rapid mapping of transcription factor-DNA interactions.
PLoS Genet. 2009 Apr;5(4):e1000449. Epub 2009 Apr 10.
Freckleton G, Lippman SI, Broach JR, Tavazoie S.

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