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Advances in Bioinformatics
Volume 2015, Article ID 909765, 10 pages
http://dx.doi.org/10.1155/2015/909765
Research Article

CISAPS: Complex Informational Spectrum for the Analysis of Protein Sequences

1Department of Genetics, University of Leicester, University Road, Leicester LE1 7RH, UK
2Department of Computer Science and Digital Technologies, Faculty of Engineering and Environment, The University of Northumbria at Newcastle, Newcastle-upon-Tyne NE1 8ST, UK
3Department of Computer Engineering, Yildiz Technical University, 34220 Istanbul, Turkey

Received 28 July 2014; Revised 27 November 2014; Accepted 4 December 2014

Academic Editor: Tatsuya Akutsu

Copyright © 2015 Charalambos Chrysostomou 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 [8 citations]

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

  • Volkan Uslan, and Huseyin Seker, “The quantitative prediction of HLA-B*2705 peptide binding affinities using Support Vector Regression to gain insights into its role for the Spondyloarthropathies,” 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 7651–7654, . View at Publisher · View at Google Scholar
  • Ferdi Sarac, Volkan Uslan, Huseyin Seker, and Ahmed Bouridane, “Comparison of unsupervised feature selection methods for high-dimensional regression problems in prediction of peptide binding affinity,” 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 8173–8176, . View at Publisher · View at Google Scholar
  • Charalambos Chrysostomou, and Huseyin Seker, “Structural classification of protein sequences based on signal processing and support vector machines,” 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3088–3091, . View at Publisher · View at Google Scholar
  • Volkan Uslan, and Huseyin Seker, “Binding affinity prediction of S. cerevisiae 14-3-3 and GYF peptide-recognition domains using support vector regression,” 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3445–3448, . View at Publisher · View at Google Scholar
  • Charalambos Chrysostomou, Harris Partaourides, and Huseyin Seker, “Prediction of Influenza A virus infections in humans using an Artificial Neural Network learning approach,” 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1186–1189, . View at Publisher · View at Google Scholar
  • Sanja Glišić, David P. Cavanaugh, Krishnan K. Chittur, Milan Sencanski, Vladimir Perovic, and Tijana Bojić, “Common molecular mechanism of the hepatic lesion and the cardiac parasympathetic regulation in chronic hepatitis C infection: a critical role for the muscarinic receptor type 3,” BMC Bioinformatics, vol. 17, no. 1, 2016. View at Publisher · View at Google Scholar
  • Volkan Uslan, and Huseyin Seker, “Quantitative prediction of peptide binding affinity by using hybrid fuzzy support vector regression,” Applied Soft Computing, 2016. View at Publisher · View at Google Scholar
  • Ailan F Arenas, Nicolás Arango-Plaza, Juan Camilo Arenas, and Gladys E Salcedo, “Time-Frequency Approach Applied to Finding Interaction Regions in Pathogenic Proteins,” Bioinformatics and Biology Insights, vol. 13, pp. 117793221985017, 2019. View at Publisher · View at Google Scholar