Skip to main content

A Genetic Programming-Based Tool for Protein Classification

Tsunoda, Denise F. and Freitas, Alex A. and Lopes, Heitor S. (2009) A Genetic Programming-Based Tool for Protein Classification. In: Abraham, Ajith and Benitez, J.M. and Herrera, F. and Loia, V. and Marcelloni, F. and Senatore, S., eds. 2009 Ninth International Conference on Intelligent Systems Design and Applications. IEEE, pp. 182-196. ISBN 978-1-4244-4735-0. (doi:10.1109/ISDA.2009.14) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/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.

Item Type: Book section
DOI/Identification number: 10.1109/ISDA.2009.14
Uncontrolled keywords: determinacy analysis, Craig interpolants; proteins; genetic programming; amino acids; evolutionary computation; sequences; biochemistry; peptides; intelligent systems; intelligent structures; data mining
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Depositing User: Alex Freitas
Date Deposited: 21 Sep 2012 09:49 UTC
Last Modified: 04 Feb 2020 04:04 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/30571 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
  • Depositors only (login required):