Prediction of DNA-binding propensity of proteins by the ball-histogram method using automatic template search - Szabóová, Andrea; Kuželka, Ondřej; Zelezný, Filip; Tolar, Jakub (BMC bioinformatics, 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.
Keywords: Protein Binding; algoritmy; aminokyseliny; Amino Acids; Monte Carlo Method; Proteins; DNA; metoda Monte Carlo; Computational Biology; Models, Theoretical; vazba proteinů; Protein Structure, Secondary; proteiny; sekundární struktura proteinů; teoretické modely; Algorithms; výpočetní biologie