Computational methods are required to identify functions of newly discovered genes, when these genes do not have sequence homologues of known function. One possible procedure rests on a statistical analysis of patterns of co-occurrence of pairs of genes in large genome sets. This project utilizes the sequences of all fully sequenced genomes. The method we are developing and testing rests on the idea that pairs of genes which co-occur more frequently than expected by chance are functionally related. New methods for mapping protein epitopes.
Epitopes are sites on proteins that interact with antibodies or other proteins.
Determining the universe of these sites is a central problem in modern biology. We are developing high speed methods for their determination, which involve both computation and experimental work. The ability to determine which portions of the human genome sequence encode receptors presently depends on sequence homology. However, many new sequences have no known homologues. This project builds on machine learning methods developed in our lab for identifying sequences that encode plasma membrane receptors.