MAHATMA: A Genetic Programming-Based Tool for Protein Classification

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Denise F. Tsunoda and Alex A. Freitas and 
                 Heitor S. Lopes",
  title =        "MAHATMA: A Genetic Programming-Based Tool for Protein
  booktitle =    "Ninth International Conference on Intelligent Systems
                 Design and Applications, ISDA '09",
  year =         "2009",
  month =        "30 " # nov # "-2 " # dec,
  pages =        "1136--1142",
  keywords =     "genetic algorithms, genetic programming, MAHATMA,
                 amino acids, biological functions, enzymes,
                 evolutionary computation method, genetic
                 programming-based tool, heuristic method, motifs,
                 protein classification, protein data bank, biology
                 computing, pattern classification, proteins",
  DOI =          "doi:10.1109/ISDA.2009.14",
  abstract =     "Proteins can be grouped into families according to
                 some features such as hydrophobicity, composition or
                 structure, aiming to establish common biological
                 functions. This paper presents a system that was
                 conceived to discover features (particular sequences of
                 amino acids, or motifs) that occur very often in
                 proteins of a given family but rarely occur in proteins
                 of other families. These features can be used for the
                 classification of unknown proteins, that is, to predict
                 their function by analyzing their primary structure.
                 Experiments were done with a set of enzymes extracted
                 from the protein data bank. The heuristic method used
                 was based on genetic programming using operators
                 specially tailored for the target problem. The final
                 performance was measured using sensitivity (Se) and
                 specificity (Sp). The best results obtained for the
                 enzyme dataset suggest that the proposed evolutionary
                 computation method is very effective to find predictive
                 features (motifs) for protein classification.",
  notes =        "Also known as \cite{5364152}",

Genetic Programming entries for Denise Fukumi Tsunoda Alex Alves Freitas Heitor Silverio Lopes