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The Scientific World Journal
Volume 2013, Article ID 347106, 8 pages
http://dx.doi.org/10.1155/2013/347106
Research Article

Extracting Physicochemical Features to Predict Protein Secondary Structure

Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, 123 University Road, Section 3, Touliu, Yunlin 640, Taiwan

Received 29 January 2013; Accepted 23 April 2013

Academic Editors: S. Jahandideh and J. Ni

Copyright © 2013 Yin-Fu Huang and Shu-Ying Chen. 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 [5 citations]

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

  • Syam B. Iryanto, Taufik Djatna, and Toto Haryanto, “Ensemble learning for protein secondary structure analysis,” 2017 International Conference on Advanced Computer Science and Information Systems (ICACSIS), pp. 409–414, . View at Publisher · View at Google Scholar
  • Bruno Grisci, and Marcio Dorn, “Predicting protein structural features with NeuroEvolution of Augmenting Topologies,” 2016 International Joint Conference on Neural Networks (IJCNN), pp. 873–880, . View at Publisher · View at Google Scholar
  • J. M. Andrade-Garda, J. R. Rabunal, J. Dorado, A. Pazos, C. Fernandez-Lozano, C. Canto, and M. Gestal, “Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification,” Scientific World Journal, 2013. View at Publisher · View at Google Scholar
  • Bruno Grisci, and M?rcio Dorn, “NEAT-FLEX: Predicting the conformational flexibility of amino acids using neuroevolution of augmenting topologies,” Journal of Bioinformatics and Computational Biology, vol. 15, no. 03, pp. 1750009, 2017. View at Publisher · View at Google Scholar
  • Katarzyna Stapor, and Piotr Fabian, “Developing a new SVM classifier for the extended ES protein structure prediction,” Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017, pp. 169–172, 2017. View at Publisher · View at Google Scholar