dc.creator | Díaz Díaz, Norberto | es |
dc.creator | Gómez Vela, Francisco | es |
dc.creator | Aguilar Ruiz, Jesús | es |
dc.creator | García Gutiérrez, Jorge | es |
dc.date.accessioned | 2022-12-12T09:13:33Z | |
dc.date.available | 2022-12-12T09:13:33Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Díaz Díaz, N., Gómez Vela, F., Aguilar Ruiz, J. y García Gutiérrez, J. (2011). Gene–Gene Interaction based Clustering method for Microarray Data. En ISDA 2011: 11th International Conference on Intelligent Systems Design and Applications (1067-1073), Córdoba, España: IEEE Computer Society. | |
dc.identifier.isbn | 978-1-4577-1676-8 | es |
dc.identifier.issn | 2164-7143 | es |
dc.identifier.issn | 2164-7151 | es |
dc.identifier.uri | https://hdl.handle.net/11441/140298 | |
dc.description.abstract | In this paper, we propose a greedy clustering
algorithm to identify groups of related genes and a new
measure to improve the results of this algorithm. Clustering
algorithms analyze genes in order to group those with similar
behavior. Instead, our approach groups pairs of genes that
present similar positive and/or negative interactions. In order to
avoid noise in clusters, we apply a threshold, the neighbouring
minimun index(λ), to know if a pair of genes have interac tion enough or not. The algorithm allows the researcher to
modify all the criteria: discretization mapping function, gene–
gene mapping function and filtering function, and even the
neighbouring minimun index, and provides much flexibility to
obtain clusters based on the level of precision needed. We have
carried out a deep experimental study in databases to obtain a
good neighbouring minimun index, λ. The performance of our
approach is experimentally tested on the yeast, yeast cell-cycle
and malaria datasets. The final number of clusters has a very
high level of customization and genes within show a significant
level of cohesion, as it is shown graphically in the experiments | es |
dc.format | application/pdf | es |
dc.format.extent | 7 | es |
dc.language.iso | eng | es |
dc.publisher | IEEE Computer Society | es |
dc.relation.ispartof | ISDA 2011: 11th International Conference on Intelligent Systems Design and Applications (2011), pp. 1067-1073. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Clustering | es |
dc.subject | Microarray analysis | es |
dc.title | Gene–Gene Interaction based Clustering method for Microarray Data | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/6121800 | es |
dc.identifier.doi | 10.1109/ISDA.2011.6121800 | es |
dc.contributor.group | Universidad de Sevilla. TIC-134: Sistemas Informáticos | es |
dc.publication.initialPage | 1067 | es |
dc.publication.endPage | 1073 | es |
dc.eventtitle | ISDA 2011: 11th International Conference on Intelligent Systems Design and Applications | es |
dc.eventinstitution | Córdoba, España | es |
dc.relation.publicationplace | New York, USA | es |