I will introduce a new method for the prediction of cis-regulatory binding sites and its application
to predicting NtcA regulated genes in cyanobacteria. The algorithm rigorously utilizes concurrence
information of multiple binding sites in the upstream region of a gene and that in the upstream regions
of its orthologues in related genomes. A probabilistic model was developed for the evaluation of prediction
reliability so that the prediction false positive rate could be well controlled. Using this method, we have
predicted multiple new members of the NtcA regulons in nine sequenced cyanobacterial genomes, and shown that
the false positive rates of the predictions have been reduced on an average of 40 fold compared to the
conventional methods. A detailed analysis of the predictions in each genome showed that a significant
portion of our predictions are consistent with previously published results about individual genes.
Bio:
Dr. Zhengchang Su received his Ph.D. in physiology and biophysics at the University of Alabama at Birmingham
in 2000, he also holds an MS in computer science from the same university. He then spent three years as a
postdoctoral fellow at Oak Ridge National Laboratory, and one year at the University of Georgia in Athens
as a research faculty. He currently is an assistant professor at the Bioinformatics Research Center of the
University of North Carolina at Charlotte. His areas of interest include deciphering gene regulatory networks
in eukaryotic and bacterial cells using genome sequences and other high throughput data, and simulating 3D
structures of membrane proteins using high performance computing.
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