dc.creator | García Nieto, José Manuel | es |
dc.creator | Alba, Enrique | es |
dc.date.accessioned | 2021-05-12T07:57:45Z | |
dc.date.available | 2021-05-12T07:57:45Z | |
dc.date.issued | 2012 | |
dc.identifier.citation | García Nieto, J.M. y Alba, E. (2012). Parallel multi-swarm optimizer for gene selection in DNA microarrays. Applied Intelligence, 37, 255-266. | |
dc.identifier.issn | 0924-669X | es |
dc.identifier.uri | https://hdl.handle.net/11441/108901 | |
dc.description.abstract | The execution of many computational steps per
time unit typical of parallel computers offers an important
benefit in reducing the computing time in real world applications.
In this work, a parallel Particle Swarm Optimization
(PSO) is used for gene selection of high dimensional
Microarray datasets. The proposed algorithm, called PMSO,
consists of running a set of independent PSOs following an
island model, where a migration policy exchanges solutions
with a certain frequency. A feature selection mechanism is
embedded in each subalgorithm for finding small samples
of informative genes amongst thousands of them. PMSO
has been experimentally assessed with different population
structures on four well-known cancer datasets. The contributions
are twofold: our parallel approach is able to
improve sequential algorithms in terms of computational
time/effort (Efficiency of 85%), as well as in terms of
accuracy rate, identifying specific genes that our work
suggests as signifi-cant ones for an accurate classification.
Additional comparisons with several recent state the of
art methods also show competitive results with improvements
of over 100% in the classification rate and very few
genes per subset. | es |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades TIN2008-06491-C04-01 | es |
dc.description.sponsorship | Junta de Andalucía P07-TIC-03044 | es |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades BES-2009-018767 | es |
dc.format | application/pdf | es |
dc.format.extent | 12 | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | Applied Intelligence, 37, 255-266. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Gene selection | es |
dc.subject | Parallel particle swarm optimization | es |
dc.subject | DNA microarrays | es |
dc.title | Parallel multi-swarm optimizer for gene selection in DNA microarrays | es |
dc.type | info:eu-repo/semantics/article | 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 Ciencias de la Computación e Inteligencia Artificial | es |
dc.relation.projectID | TIN2008-06491-C04-01 | es |
dc.relation.projectID | P07-TIC-03044 | es |
dc.relation.projectID | BES-2009-018767 | es |
dc.relation.publisherversion | https://link.springer.com/article/10.1007/s10489-011-0325-9 | es |
dc.identifier.doi | 10.1007/s10489-011-0325-9 | es |
dc.journaltitle | Applied Intelligence | es |
dc.publication.volumen | 37 | es |
dc.publication.initialPage | 255 | es |
dc.publication.endPage | 266 | es |
dc.contributor.funder | Ministerio de Ciencia, Innovación y Universidades (MICINN). España | es |
dc.contributor.funder | Junta de Andalucía | es |