title: A comment on "Prediction of protein structural classes by a new measure of information discrepancy".
abstract: Protein structural class describes the overall folding type of a protein or its domain. A number of methods were developed to predict protein structural class based on its primary sequence. The homology of the predicted sequences with respect to the training sequences is a key attribute for the prediction performance. In this article we investigated the FDOD method developed by Jin et al. [Jin, L., Fang, W., Tang, H., 2003. Prediction of protein structural classes by a new measure of information discrepancy. Comput. Biol. Chem. 27, 373-380], which gave high prediction accuracy on a low homology dataset, and we empirically confirmed that the reported results were an artifact of improper implementation.
authors.affiliation: Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alta., Canada.
authors.forename: Kanaka Durga
authors.initials: KD
authors.lastname: Kedarisetti
authors.forename: Lukasz
authors.initials: L
authors.lastname: Kurgan
authors.forename: Scott
authors.initials: S
authors.lastname: Dick
mesh_terms: D003198:Computer Simulation; D030562:Databases, Protein; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000145:classification
chemical_list: D011506:Proteins