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Statistical Test-Based Evolutionary Segmentation of Yeast Genome

Opened Access Statistical Test-Based Evolutionary Segmentation of Yeast Genome

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Autor: Aguilar Ruiz, Jesús Salvador
Mateos García, Daniel
Giráldez Rojo, Raúl
Riquelme Santos, José Cristóbal
Departamento: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Fecha: 2004
Publicado en: Genetic and Evolutionary Computation – GECCO 2004, Lecture Notes in Computer Science, Volume 3102, pp 493-494 (2004)
Tipo de documento: Capítulo de Libro
Resumen: Segmentation algorithms emerge observing fluctuations of DNA sequences in alternative homogeneous domains, which are named segments [1]. The key idea is that two genes that are controlled by a single regulatory system should have similar expression patterns in any data set. In this work, we present a new approach based on Evolutionary Algorithms (EAs) that differentiate segments of genes, which are represented by its level of meiotic recombination. We have tested the algorithm with the yeast genome [2][3] because this organism is very interesting for the research community, as it preserves many biological properties from more complex organisms and it is simple enough to run experiments. We have a file with about 6100 genes, divided into sixteen yeast chromosomes (N). Each gene is a row of the file. Each column of file represents a genomic characteristic under speci.c conditions (in this case, only the activity of meiotic recombination). The goal is to group consecutive genes properly ...
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Tamaño: 63.04Kb
Formato: PDF

URI: http://hdl.handle.net/11441/39698

DOI: http://dx.doi.org/10.1007/978-3-540-24854-5_49

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