Prediction of protein interaction sites from sequence profile and residue neighbor list

By Huan‐Xiang Zhou, Yibing Shan. Proteins: Structure, Function, and Bioinformatics, 2001

324 citations recorded by the source corpus.

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Exploiting sequence and structure homologs to identify protein–protein binding sites (2005, unknown): “The nonredundant chains of hetero-complexes were selected by the method of Zhou et al. 35 with the following modiﬁcations.”
Improved prediction of protein-protein binding sites using a support vector machines approach. (2005, background): “…differentiates interfaces from other surface patches (Jones and Thornton, 1997a), so a number of studies have attempted to combine more than one of these physical– chemical properties (Keil et al., 2004; Fariselli et al., 2002; Zhou and Shan, 2001; Jones and Thornton, 1997b; Neuvirth et al., 2004).”
Applying the Naïve Bayes classifier with kernel density estimation to the prediction of protein-protein interaction sites (2010, background): “Zhou and Shan (2001) and Fariselli et al. (2002) © The Author 2010.”
Analysing six types of protein-protein interfaces. (2003, background): “Other studies reported that salt-bridges are not an important factor in protein–protein interaction,(9) or that interfaces favour non-polar residues.(23) The detailed separation of six types of interfaces explained these contradictions: while we identified some general trends, most of the residuessh”
Machine Learning Methods for Protein Structure Prediction (2008, methodology): “Currently, neural networks, HMMs and support vector machine methods have been used to predict interface sites [114].”