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The Scientific World Journal
Volume 2014, Article ID 240673, 7 pages
Research Article

Prediction of Protein-Protein Interaction Strength Using Domain Features with Supervised Regression

1Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan
2Japan Ichiba Section Development Unit, Rakuten Inc., 4-12-3 Higashi-shinagawa, Shinagawa-ku, Tokyo 140-0002, Japan
3Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan

Received 3 April 2014; Accepted 30 May 2014; Published 24 June 2014

Academic Editor: Loris Nanni

Copyright © 2014 Mayumi Kamada 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 [4 citations]

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

  • Dongliang Xu, Jingchang Pan, Bailing Wang, and Xinyi Zou, “Biological entity relationship extraction method based on multiple kernel learning,” 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 1669–1672, . View at Publisher · View at Google Scholar
  • Xu Dongliang, Wang Bailing, and Pan Jingchang, “Multiple kernels learning-based biological entity relationship extraction method,” Journal of Biomedical Semantics, vol. 8, 2017. View at Publisher · View at Google Scholar
  • Le Ou-Yang, Hong Yan, and Xiao-Fei Zhang, “A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks,” BMC Bioinformatics, vol. 18, 2017. View at Publisher · View at Google Scholar
  • Renu Vyas, Sanket Bapat, Purva Goel, Muthukumarasamy Karthikeyan, Sanjeev S. Tambe, and Bhaskar D. Kulkarni, “Application of Genetic Programming (GP) Formalism for Building Disease Predictive Models from Protein-Protein Interactions (PPI) Data,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 15, no. 1, pp. 27–37, 2018. View at Publisher · View at Google Scholar