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Nucleic Acids Res. 2015 Dec 2;43(21):10180-9. doi: 10.1093/nar/gkv1134. Epub 2015 Nov 2.

Computational learning on specificity-determining residue-nucleotide interactions.

Author information

1
Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong kc.w@cityu.edu.hk.
2
Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada CSAIL, Massachusetts Institute of Technology, Cambridge, MA 02139-4307, USA.
3
CEMSE Division, King Abdullah University of Science and Technology, Thuwal, Jeddah, Saudi Arabia.
4
Department of Cell and Systems Biology, University of Toronto, Toronto, Ontario, Canada Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.
5
Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada zhaolei.zhang@utoronto.ca.

Abstract

The protein-DNA interactions between transcription factors and transcription factor binding sites are essential activities in gene regulation. To decipher the binding codes, it is a long-standing challenge to understand the binding mechanism across different transcription factor DNA binding families. Past computational learning studies usually focus on learning and predicting the DNA binding residues on protein side. Taking into account both sides (protein and DNA), we propose and describe a computational study for learning the specificity-determining residue-nucleotide interactions of different known DNA-binding domain families. The proposed learning models are compared to state-of-the-art models comprehensively, demonstrating its competitive learning performance. In addition, we describe and propose two applications which demonstrate how the learnt models can provide meaningful insights into protein-DNA interactions across different DNA binding families.

PMID:
26527718
PMCID:
PMC4666365
DOI:
10.1093/nar/gkv1134
[Indexed for MEDLINE]
Free PMC Article

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