Prediction of DNA-binding propensity of proteins by the ball-histogram method

Andrea Szabóová, Ondřej Kuželka, Sergio Morales E., Filip Železný, Jakub Tolar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 the charged patches of the proteins, the ball-histogram technique enables a systematic, Monte-Carlo exploration of the spatial distribution of charged amino acids, capturing joint probabilities of specified amino acids occurring in certain distances from each other. This exploration yields a model for the prediction of DNA binding propensity. We validate our method in prediction experiments, achieving favorable accuracies. Moreover, our method also provides interpretable features involving spatial distributions of selected amino acids.

Original languageEnglish (US)
Title of host publicationBioinformatics Research and Applications - 7th International Symposium, ISBRA 2011, Proceedings
Pages358-367
Number of pages10
DOIs
StatePublished - May 16 2011
Event7th International Symposium on Bioinformatics Research and Applications, ISBRA 2011 - Changsha, China
Duration: May 27 2011May 29 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6674 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Symposium on Bioinformatics Research and Applications, ISBRA 2011
CountryChina
CityChangsha
Period5/27/115/29/11

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