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Capítulo de Libro
Statistical Test-Based Evolutionary Segmentation of Yeast Genome
dc.creator | Aguilar Ruiz, Jesús Salvador | es |
dc.creator | Mateos García, Daniel | es |
dc.creator | Giráldez Rojo, Raúl | es |
dc.creator | Riquelme Santos, José Cristóbal | es |
dc.date.accessioned | 2016-04-07T10:05:45Z | |
dc.date.available | 2016-04-07T10:05:45Z | |
dc.date.issued | 2004 | |
dc.identifier.uri | http://hdl.handle.net/11441/39698 | |
dc.description.abstract | 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 differentiated from adjacent segments. Each group will be a segment of genes, as it will maintain the physical location within the genome. To measure the relevance of segments the Mann–Whitney statistical test has been used. | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.relation.ispartof | Genetic and Evolutionary Computation – GECCO 2004, Lecture Notes in Computer Science, Volume 3102, pp 493-494 (2004) | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Algorithm analysis | es |
dc.subject | Artificial intelligence | es |
dc.subject | Bioinformatics | es |
dc.subject | Processor architectures | es |
dc.title | Statistical Test-Based Evolutionary Segmentation of Yeast Genome | es |
dc.type | info:eu-repo/semantics/bookPart | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.identifier.doi | http://dx.doi.org/10.1007/978-3-540-24854-5_49 | es |
dc.identifier.idus | https://idus.us.es/xmlui/handle/11441/39698 |
Ficheros | Tamaño | Formato | Ver | Descripción |
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Statistical test.pdf | 63.04Kb | [PDF] | Ver/ | |