Repositorio de producción científica de la Universidad de Sevilla

Revisiting the Yeast Cell Cycle Problem with the Improved TriGen Algorithm

Opened Access Revisiting the Yeast Cell Cycle Problem with the Improved TriGen Algorithm


buscar en

Exportar a
Autor: Gutiérrez Avilés, David
Rubio Escudero, Cristina
Riquelme Santos, José Cristóbal
Departamento: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Fecha: 2011
Publicado en: Third World Congress on Nature & Biologically Inspired Computing, NaBIC 2011, Salamanca, Spain, October 19-21, 2011. IEEE 2011
ISBN/ISSN: 978-1-4577-1122-0
Tipo de documento: Capítulo de Libro
Resumen: Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior under the conditions tested. Biclustering emerges as an improvement of classical clustering since it relaxes the constraints for grouping allowing genes to be evaluated only under a subset of the conditions and not under all of them. However, this technique is not appropriate for the analysis of temporal microarray data in which the genes are evaluated under certain conditions at several time points. On a previous work we presented the TriGen algorithm, a genetic algorithm that finds triclusters of gene expression that take into account the experimental conditions and the time points simultaneously, and was applied to the yeast (Saccharomyces Cerevisiae) cell cycle problem. In this article we present some improvements on the genetic algorithm and we also present the re...
[Ver más]
Tamaño: 180.9Kb
Formato: PDF



Mostrar el registro completo del ítem

Esta obra está bajo una Licencia Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internacional

Este registro aparece en las siguientes colecciones