title: Prediction of DNA-binding propensity of proteins by the ball-histogram method using automatic template search.
abstract: We contribute a novel, ball-histogram approach to DNA-binding propensity prediction of proteins. Unlike state-of-the-art methods based on constructing an ad-hoc set of features describing physicochemical properties of the proteins, the ball-histogram technique enables a systematic, Monte-Carlo exploration of the spatial distribution of amino acids complying with automatically selected properties. This exploration yields a model for the prediction of DNA binding propensity. We validate our method in prediction experiments, improving on state-of-the-art accuracies. Moreover, our method also provides interpretable features involving spatial distributions of selected amino acids.
authors: Czech Technical University, Department of Cybernetics, Prague, 166 27, Czech Republic. szaboand@fel.cvut.cz
authors: Andrea
authors: A
authors: Szabóová
authors: Ondřej
authors: O
authors: Kuželka
authors: Filip
authors: F
authors: Zelezný
authors: Jakub
authors: J
authors: Tolar
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000032:analysis; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000032:analysis*; D008962:Models, Theoretical; D009010:Monte Carlo Method; D011485:Protein Binding; D017433:Protein Structure, Secondary; D011506:Proteins / Q000032:analysis*
chemical_list: D000596:Amino Acids; D011506:Proteins; D004247:DNA