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Microarray classification with hierarchical data representation and novel feature selection criteria
dc.contributor.author | Bosio, Mattia |
dc.contributor.author | Bellot Pujalte, Pau |
dc.contributor.author | Salembier Clairon, Philippe Jean |
dc.contributor.author | Oliveras Vergés, Albert |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2013-03-13T19:48:02Z |
dc.date.created | 2012 |
dc.date.issued | 2012 |
dc.identifier.citation | Bosio, M. [et al.]. Microarray classification with hierarchical data representation and novel feature selection criteria. A: IEEE International Conference on BioInformatics and BioEngineering. "Proceedings of the 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE) : Larnaca, Cyprus, 11-13 November 2012". Larnaca: Institute of Electrical and Electronics Engineers (IEEE), 2012, p. 344-349. |
dc.identifier.isbn | 978-1-4673-4358-9 |
dc.identifier.uri | http://hdl.handle.net/2117/18291 |
dc.description.abstract | Microarray data classification is a challenging prob- lem due to the high number of variables compared to the small number of available samples. An effective methodology to output a precise and reliable classifier is proposed in this work as an improvement of the algorithm in [1]. It considers the sample scarcity problem and the lack of data structure typical of microarrays. Both problem are assessed by a two-step approach applying hierarchical clustering to create new features called metagenes and introducing a novel feature ranking criterion, inside the wrapper feature selection task. The classification ability has been evaluated on 4 publicly available datasets from Micro Array Quality Control study phase II (MAQC) classified by 7 different endpoints. The global results have showed how the proposed approach obtains better prediction accuracy than a wide variety of state of the art alternatives |
dc.format.extent | 6 p. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
dc.subject.lcsh | Bioinformatics |
dc.subject.lcsh | Biology -- Data processing |
dc.title | Microarray classification with hierarchical data representation and novel feature selection criteria |
dc.type | Conference report |
dc.subject.lemac | Bioinformàtica |
dc.subject.lemac | Biologia -- Informàtica |
dc.contributor.group | Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo |
dc.identifier.doi | 10.1109/BIBE.2012.6399648 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6399648&tag=1 |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 11152473 |
dc.description.version | Postprint (published version) |
dc.date.lift | 10000-01-01 |
local.citation.author | Bosio, M.; Bellot, P.; Salembier, P.; Oliveras, A. |
local.citation.contributor | IEEE International Conference on BioInformatics and BioEngineering |
local.citation.pubplace | Larnaca |
local.citation.publicationName | Proceedings of the 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE) : Larnaca, Cyprus, 11-13 November 2012 |
local.citation.startingPage | 344 |
local.citation.endingPage | 349 |