The primary focus of this component of the Resource is to apply pattern recognition methods to discover regulatory elements, such as transcription factor binding sites, in sets of co-regulated genes. We have not yet gotten datasets from the DNA array group for analysis. However, we have been assessing the ability of our programs to identify the correct functional domains in yeast promoters using collections of genes with known regulatory sites. The controls have allowed us to test different approaches and to make refinements to to improve their detection capability. We have also obtain a couple of experimental datasets from Pat Brown and have run analyses on those as further tests of the methods to reliably identify regulatory sites. We have also explored the ability of our methods to elucidate cooperative interactions when multiple proteins are involved in the regulation. We have done this using data from the MetJ repressor from E. coli because adequate data exist for this analysis. A paper describing these results has been submitted. We think that the ability to detect multiple binding sites and account for their cooperative interactions will be important for some yeast genes, and the approach we've adopted and refined on an E. coli example is useful experience and preparation. We have also been developing and refining an adaptation of our method to specifically identify motifs involved in protein-protein interactions. For this we have used data on MHC-peptide interactions to identify the sub-domain being recognized and to model the energetic contributions of individual amino acids. This method appears to be working well and will be further refined with additional datasets. We think this method will be applicable to other types of data concerning protein-protein interactions, specifically for the identification of motifs that allow for docking of the proteins into complexes.
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