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The Scientific World Journal
Volume 2014 (2014), Article ID 464093, 6 pages
http://dx.doi.org/10.1155/2014/464093
Research Article

Protein Binding Site Prediction by Combining Hidden Markov Support Vector Machine and Profile-Based Propensities

1School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, China
2Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, China
3School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China

Received 4 June 2014; Accepted 1 July 2014; Published 14 July 2014

Academic Editor: Wei Chen

Copyright © 2014 Bin Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [10 citations]

The following is the list of published articles that have cited the current article.

  • Reyhaneh Esmaielbeiki, Konrad Krawczyk, Bernhard Knapp, Jean-Christophe Nebel, and Charlotte M. Deane, “Progress and challenges in predicting protein interfaces,” Briefings in Bioinformatics, vol. 17, no. 1, pp. 117–131, 2015. View at Publisher · View at Google Scholar
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  • Leyi Wei, Quan Zou, Minghong Liao, Huijuan Lu, and Yuming Zhao, “A Novel Machine Learning Method for Cytokine-Receptor Interaction Prediction,” Combinatorial Chemistry & High Throughput Screening, vol. 19, no. 2, pp. 144–152, 2016. View at Publisher · View at Google Scholar
  • Zhao-Chun Xu, Shi-Yu Jiang, Wang-Ren Qiu, Ying-Chun Liu, and Xuan Xiao, “iDHSs-PseTNC: Identifying DNase I hypersensitive sites with pseuo trinucleotide component by deep sparse auto-encoder,” Letters in Organic Chemistry, vol. 14, no. 9, pp. 655–664, 2017. View at Publisher · View at Google Scholar
  • Hui Li, Dechang Pi, Yaling Wu, and Chuanming Chen, “Integrative Method Based on Linear Regression for the Prediction of Zinc-Binding Sites in Proteins,” IEEE Access, vol. 5, pp. 14647–14656, 2017. View at Publisher · View at Google Scholar