title: Prediction of chemical-protein binding activity using contrast graph patterns.
abstract: The problem of classifying chemical compounds is studied in this chapter. Compounds are represented as two-dimensional topological graphs of atoms (corresponding to nodes) and bonds (corresponding to edges). We use a method called contrast common pattern classifier (CCPC) to predict chemical-protein binding activity. This approach is strongly associated with the classical emerging patterns techniques known from decision tables. It uses two different types of structural patterns (subgraphs): contrast and common. Results show that the considered algorithm outperforms all other existing methods in terms of classification accuracy.
authors: Institute of Radioelectronics, Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warsaw, Poland. a.dominik@elka.pw.edu.pl
authors: Andrzej
authors: A
authors: Dominik
authors: Zbigniew
authors: Z
authors: Walczak
authors: Jacek
authors: J
authors: Wojciechowski
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D003196:Computer Graphics; D003198:Computer Simulation; D016208:Databases, Factual; D004353:Drug Evaluation, Preclinical; D010363:Pattern Recognition, Automated; D004364:Pharmaceutical Preparations / Q000737:chemistry* / Q000145:classification / Q000378:metabolism*; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D014584:User-Computer Interface
chemical_list: D004364:Pharmaceutical Preparations