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Hierarchical clustering combining numerical and biological similarities for gene expression data classification
dc.contributor.author | Bosio, Mattia |
dc.contributor.author | Salembier Clairon, Philippe Jean |
dc.contributor.author | Bellot Pujalte, Pau |
dc.contributor.author | Oliveras Vergés, Albert |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2016-05-06T12:31:26Z |
dc.date.issued | 2013 |
dc.identifier.citation | Bosio, M., Salembier, P., Bellot, P., Oliveras, A. Hierarchical clustering combining numerical and biological similarities for gene expression data classification. A: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. "Conference proceedings : 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference". Osaka: Institute of Electrical and Electronics Engineers (IEEE), 2013, p. 584-587. |
dc.identifier.isbn | 978-1-4577-0214-3 |
dc.identifier.uri | http://hdl.handle.net/2117/86695 |
dc.description.abstract | High throughput data analysis is a challenging problem due to the vast amount of available data. A major concern is to develop algorithms that provide accurate numerical predictions and biologically relevant results. A wide variety of tools exist in the literature using biological knowledge to evaluate analysis results. Only recently, some works have included biological knowledge inside the analysis process improving the prediction results. |
dc.format.extent | 4 p. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
dc.subject.lcsh | Algorithms |
dc.subject.lcsh | Bioinformatics |
dc.subject.other | Algorithm design and analysis |
dc.subject.other | Bioinformatics |
dc.subject.other | Clustering algorithms |
dc.subject.other | Databases |
dc.subject.other | Genomics |
dc.subject.other | Prediction algorithms |
dc.title | Hierarchical clustering combining numerical and biological similarities for gene expression data classification |
dc.type | Conference report |
dc.subject.lemac | Algorismes |
dc.subject.lemac | Bioinformàtica |
dc.contributor.group | Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo |
dc.identifier.doi | 10.1109/EMBC.2013.6609567 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6609567 |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 12893280 |
dc.description.version | Postprint (published version) |
dc.date.lift | 10000-01-01 |
local.citation.author | Bosio, M.; Salembier, P.; Bellot, P.; Oliveras, A. |
local.citation.contributor | Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
local.citation.pubplace | Osaka |
local.citation.publicationName | Conference proceedings : 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference |
local.citation.startingPage | 584 |
local.citation.endingPage | 587 |