Protein secondary structure prediction using an evolutionary computation method and clustering

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@InProceedings{Zamani:2015:CIBCB,
  author =       "Masood Zamani and Stefan C. Kremer",
  booktitle =    "2015 IEEE Conference on Computational Intelligence in
                 Bioinformatics and Computational Biology (CIBCB)",
  title =        "Protein secondary structure prediction using an
                 evolutionary computation method and clustering",
  year =         "2015",
  abstract =     "In this paper, we evaluated the performance of an
                 evolutionary-based protein secondary structure (PSS)
                 prediction model which uses the information of amino
                 acid sequences extracted by a clustering technique. The
                 dimension of the classifier's inputs is reduced using a
                 k-means clustering method on sequence segments. The
                 proposed PSS classifier is based on a Genetic
                 Programming (GP) approach that uses IF rules for a
                 multi-target classifier. The GP classifier is evaluated
                 by using protein sequences and the sequence information
                 obtained from the k-means clustering. The GP prediction
                 model's performance is compared with those of
                 feed-forward artificial neural networks (ANNs) and
                 support vector machines (SVMs). The prediction methods
                 are examined with two protein datasets RS126 and CB513.
                 The performance of the three classification models are
                 measured according to Q3 and segment overlap (SOV)
                 scores. The prediction models which use clustered data
                 result in average 2percent higher prediction accuracy
                 than those using sequence data. In addition, the
                 experimental results indicate the GP model's prediction
                 scores are in average 3percent higher than those of the
                 ANN and SVMs models when amino acid sequences or
                 clustered information are explored.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CIBCB.2015.7300327",
  month =        aug,
  notes =        "Sch. of Comput. Sci., Univ. of Guelph, Guelph, ON,
                 Canada

                 Also known as \cite{7300327}",
}

Genetic Programming entries for Masood Zamani Stefan C Kremer

Citations