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

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, si...

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Detalles Bibliográficos
Autores principales: Zwir, I., Romero Zaliz, R.
Formato: CONF
Materias:
Biological Sequences
Fuzzy Logic
Generalized Clustering
Genetic Algorithms
Pareto Optimality
Pattern Recognition
Automation
Computational methods
Data mining
DNA
Fuzzy sets
Genetic algorithms
Identification (control systems)
Optimization
Pareto principle
Problem solving
Societies and institutions
Biological sequences
Generalized clustering
Pareto optimality
Pattern recognition
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_09707890_v6_n_p586_Zwir
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
Descripción
Sumario: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.

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