dc.creator | Nepomuceno Chamorro, Juan Antonio | es |
dc.creator | Troncoso Lora, Alicia | es |
dc.creator | Nepomuceno Chamorro, Isabel de los Ángeles | es |
dc.creator | Aguilar Ruiz, Jesús Salvador | es |
dc.date.accessioned | 2022-05-27T08:34:29Z | |
dc.date.available | 2022-05-27T08:34:29Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Nepomuceno Chamorro, J.A., Troncoso Lora, A., Nepomuceno Chamorro, I.d.l.Á. y Aguilar Ruiz, J.S. (2015). Integrating biological knowledge based on functional annotations for biclustering of gene expression data. Computer Methods and Programs in Biomedicine, 119 (3), 163-180. | |
dc.identifier.issn | 0169-2607 | es |
dc.identifier.uri | https://hdl.handle.net/11441/133790 | |
dc.description.abstract | Gene expression data analysis is based on the assumption that co-expressed genes imply
co-regulated genes. This assumption is being reformulated because the co-expression of a
group of genes may be the result of an independent activation with respect to the same
experimental condition and not due to the same regulatory regime. For this reason, tradi tional techniques are recently being improved with the use of prior biological knowledge
from open-access repositories together with gene expression data.
Biclustering is an unsupervised machine learning technique that searches patterns in
gene expression data matrices. A scatter search-based biclustering algorithm thatintegrates
biological information is proposed in this paper. In addition to the gene expression data
matrix, the input of the algorithm is only a direct annotation file that relates each gene to a
set of terms from a biological repository where genes are annotated. Two different biolog ical measures, FracGO and SimNTO, are proposed to integrate this information by means
of its addition to-be-optimized fitness function in the scatter search scheme. The measure
FracGO is based on the biological enrichment and SimNTO is based on the overlapping
among GO annotations of pairs of genes. Experimental results evaluate the proposed algo rithm for two datasets and show the algorithm performs better when biological knowledge
is integrated. Moreover, the analysis and comparison between the two different biological
measures is presented and it is concluded that the differences depend on both the data
source and how the annotation file has been built in the case GO is used. It is also shown
that the proposed algorithm obtains a greater number of enriched biclusters than other
classical biclustering algorithms typically used as benchmark and an analysis of the over lapping among biclusters reveals that the biclusters obtained present a low overlapping.
The proposed methodology is a general-purpose algorithm which allows the integration
of biological information from several sources and can be extended to other biclustering
algorithms based on the optimization of a merit function. | es |
dc.description.sponsorship | Ministerio de Ciencia e Innovación TIN2011-28956-C02-02 | es |
dc.description.sponsorship | Junta de Andalucía P12-TIC-1728 | es |
dc.description.sponsorship | Universidad Pablo de Olavide APPB813097 | es |
dc.format | application/pdf | es |
dc.format.extent | 18 | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | Computer Methods and Programs in Biomedicine, 119 (3), 163-180. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Biclustering of gene expression data | es |
dc.subject | Integration of biological knowledge | es |
dc.subject | Scatter Search | es |
dc.title | Integrating biological knowledge based on functional annotations for biclustering of gene expression data | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | 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.projectID | TIN2011-28956-C02-02 | es |
dc.relation.projectID | P12-TIC-1728 | es |
dc.relation.projectID | APPB813097 | es |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0169260715000450?via%3Dihub | es |
dc.identifier.doi | 10.1016/j.cmpb.2015.02.010 | es |
dc.journaltitle | Computer Methods and Programs in Biomedicine | es |
dc.publication.volumen | 119 | es |
dc.publication.issue | 3 | es |
dc.publication.initialPage | 163 | es |
dc.publication.endPage | 180 | es |
dc.identifier.sisius | 20847771 | es |
dc.contributor.funder | Ministerio de Ciencia e Innovación (MICIN). España | es |
dc.contributor.funder | Junta de Andalucía | es |
dc.contributor.funder | Universidad Pablo de Olavide | es |