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Predicting DNA-binding sites of proteins from amino acid sequence

Authors:	Changhui Yan Michael Terribilini Feihong Wu Robert L Jernigan Drena Dobbs and Vasant Honavar

Institution:	(1) Department of Computer Science, Utah State University, Logan, Utah 84341, USA;(2) Department of Genetics, Development and Cell Biology, Iowa State University, Ames, Iowa 50010, USA;(3) Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, Iowa 50010, USA;(4) Artificial Intelligence Research Laboratory, Iowa State University, Ames, Iowa 50010, USA;(5) Department of Computer Science, Iowa State University, Ames, Iowa 50010, USA;(6) Center for Computational Intelligence, Learning, and Discovery, Iowa State University, Ames, Iowa 50010, USA;(7) Laurence H Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, Iowa 50010, USA;(8) Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, Iowa 50010, USA

Abstract:	Background Understanding the molecular details of protein-DNA interactions is critical for deciphering the mechanisms of gene regulation. We present a machine learning approach for the identification of amino acid residues involved in protein-DNA interactions.

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