"Remote homology inference: what are the limits?"

Nick Grishin
University of Texas, Southwestern Medical Center

Approaches integrating sequence, structure and functional information with evolutionary considerations have been proven to be most efficient for understanding weak similarities between proteins. Several examples of remote homology inference using combination of computational methods will be discussed. In particular, power of transitive sequence similarity searches in reliable detection of homologs at close to and below random sequence identity will be illustrated. Pairs of proteins with statistically supported sequence similarity that adopt different structural folds will be shown.

Back to Long Programs