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Inferring Gene-Gene Associations from Quantitative Association Rules

Opened Access Inferring Gene-Gene Associations from Quantitative Association Rules


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Autor: Martínez Ballesteros, María del Mar
Nepomuceno Chamorro, Isabel de los Ángeles
Riquelme Santos, José Cristóbal
Departamento: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Fecha: 2011
Publicado en: Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications 22 – 24 November 2011 Córdoba, Spain
ISBN/ISSN: 978-1-4577-1676-8
Tipo de documento: Capítulo de Libro
Resumen: The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The interest in this technique has grown exponentially in recent years and the difficulties in analyzing data from such experiments, which are characterized by the high number of genes to be analyzed in relation to the low number of experiments or samples available. Microarray experiments are generating datasets that can help in reconstructing gene networks. One of the most important problems in network reconstruction is finding, for each gene in the network, which genes can affect it and how. Association Rules are an approach of unsupervised learning to relate attributes to each other. In this work we use Quantitative Association Rules in order to define interrelations between genes. These rules work with intervals on the attributes, without discretizing the data before and they are generated by a multi-objective evolutionary algorithm. In most cases th...
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