Research Abstract:
My group does both computational and experimental biology. Most of the experimental work is focused on understanding the regulation of gene expression, and especially the basis of specificity in protein-nucleic acid interactions. We analyze how the affinity of proteins for DNA changes depending on the sequence of the DNA, and conversely for changes in the key residues of the protein. We have developed methods that allow us to obtain accurate, quantitative data in large amounts, which can be used to develop models for the interactions.
Much of the computational work is also involved with modeling protein-nucleic acid interactions, and relies on a close collaboration with the experimental work. Recently, we have focused on developing algorithms that can combine different types of data, including phylogenetic conservation and expression measurements, to help discover regualtory patterns. In addition, we have been developing new methods for RNA structure prediction and identifying RNA motifs involved in post-transcriptional gene regulation. We use comparative data from multiple, related species and pattern recognition algorithms to help uncover genetic regulatory networks.
Selected Publications:
Xu X, Ji Y, Stormo GD. RNA Sampler: A new sampling based algorithm for common RNA secondary structure prediction and structural alignment. Bioinformatics 2007 23:1883-1891.
Zhao G, Schriefer LA, Stormo GD. Identification of muscle-specific regulatory modules in Caenorhabditis elegans. Genome Res 2007 17:348-357.
Chang L-W, Nagarajan R, Magee JA, Milbrandt J and Stormo GD. Predicting Transcriptional Regulatory Mechanisms by Systematic Promoter Analysis. Genome Res 2006 16:405-413.
Tan K, McCue LA, Stormo GD. Making whole genome connections between transcription factors and their DNA binding motifs. Genome Res 2005 15:312-320.
Wang T and Stormo GD. Identifying conserved regulatory networks in a eukaryotic genome. Proc Natl Acad Sci 2005 102:17400-17405.
Last Updated: 09/05/2007 |