Automated Biological Sequence description and recognition by a localized multiobjective genetic algorithm

I. Zwir, R. Romero Zaliz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A Pareto genetic algorithm for automated biological sequence description and recognition was presented. The methods for the description of features lying the effective frontier or the set of all Pareto-optimal solutions of a multiobjective problem were discussed. An approach based on elimination, simplification and clustering techniques to summarize and organize the Pareto-optimal solutions was introduced. The experimental results of the application of the methodology to the description of DNA sequences were also presented.

Original languageEnglish
Title of host publicationProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002
EditorsJ.H. Caulfield, S.H. Chen, H.D. Cheng, R. Duro, J.H. Caufield, S.H. Chen, H.D. Cheng, R. Duro, V. Honavar
Pages586-589
Number of pages4
StatePublished - Dec 1 2002
Externally publishedYes
EventProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002 - Research Triange Park, NC, United States
Duration: Mar 8 2002Mar 13 2002

Publication series

NameProceedings of the Joint Conference on Information Sciences
Volume6

Conference

ConferenceProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002
CountryUnited States
CityResearch Triange Park, NC
Period03/8/0203/13/02

Keywords

  • Biological Sequences
  • Fuzzy Logic
  • Generalized Clustering
  • Genetic Algorithms
  • Pareto Optimality
  • Pattern Recognition

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