Semantic mining in clusters from signaling pathways networks

Please use this identifier to cite or link to this item: http://dspace.utpl.edu.ec/handle/123456789/18749

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DC Field	Value	Language
dc.contributor.author	Aguilar Castro, J.	es_ES
dc.date.accessioned	2017-06-16T22:02:18Z	-
dc.date.available	2017-06-16T22:02:18Z	-
dc.date.issued	2015-12-16	es_ES
dc.identifier	10.1109/CLEI.2015.7359986	es_ES
dc.identifier.issn	978-146739143-6	es_ES
dc.identifier.other	10.1109/CLEI.2015.7359986	es_ES
dc.identifier.uri	http://dspace.utpl.edu.ec/handle/123456789/18749	-
dc.description.abstract	This paper describes how to semantically enrich clusters from signaling pathways networks. The study is divided into two phases, the first is the detection of clusters in signaling pathways networks, after getting these clusters, they are passed to an extraction process of centrality within each one, so the second phase can enrich them semantically. The centrality chosen for the case study is the measure of closeness to other nodes, and it is who is enriched semantically in each cluster. The selected case study is the signaling pathway of TGF-?, and the central nodes found were enriched with the Gene Ontology. © 2015 IEEE.	es_ES
dc.language	Portugués	es_ES
dc.subject	Bioinformatics	es_ES
dc.subject	clustering	es_ES
dc.subject	Ontology Mining	es_ES
dc.subject	semantic enrichment	es_ES
dc.subject	TGF-?	es_ES
dc.title	Semantic mining in clusters from signaling pathways networks	es_ES
dc.type	Article	es_ES
dc.publisher	Proceedings - 2015 41st Latin American Computing Conference, CLEI 2015	es_ES
Appears in Collections:	Artículos de revistas Científicas

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