This article is part of the supplement: Selected articles from the 7th International Symposium on Bioinformatics Research and Applications (ISBRA'11)
Prediction of DNA-binding propensity of proteins by the ball-histogram method using automatic template search
1 Czech Technical University, Department of Cybernetics, Prague, 166 27, Czech Republic
2 University of Minnesota, Department of Pediatrics, Blood and Marrow Transplantation, Minneapolis, USA
BMC Bioinformatics 2012, 13(Suppl 10):S3 doi:10.1186/1471-2105-13-S10-S3Published: 25 June 2012
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.