Background: One of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because ...
Background: The function of a novel gene product is typically predicted by transitive assignment of annotation from similar sequences. We describe a novel method, GOtcha, for pred...
David M. A. Martin, Matthew Berriman, Geoffrey J. ...
Background: Remote homology detection is a challenging problem in Bioinformatics. Arguably, profile Hidden Markov Models (pHMMs) are one of the most successful approaches in addre...
Background: Prediction of transmembrane (TM) helices by statistical methods suffers from lack of sufficient training data. Current best methods use hundreds or even thousands of f...
Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure predict...
Blaise Gassend, Charles W. O'Donnell, William Thie...