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dc.contributor.authorKayano, Mitsunorien
dc.contributor.authorTakigawa, Ichigakuen
dc.contributor.authorShiga, Motokien
dc.contributor.authorTsuda, Kojien
dc.contributor.authorMamitsuka, Hiroshien
dc.contributor.alternative馬見塚, 拓ja
dc.date.accessioned2012-06-26T02:26:03Z-
dc.date.available2012-06-26T02:26:03Z-
dc.date.issued2011-06-
dc.identifier.issn0305-1048-
dc.identifier.urihttp://hdl.handle.net/2433/156792-
dc.description.abstractA switching mechanism in gene expression, where two genes are positively correlated in one condition and negatively correlated in the other condition, is a key to elucidating complex biological systems. There already exist methods for detecting switching mechanisms from microarrays. However, current approaches have problems under three real cases: outliers, expression values with a very small range and a small number of examples. ROS-DET overcomes these three problems, keeping the computational complexity of current approaches. We demonstrated that ROS-DET outperformed existing methods, under that all these three situations are considered. Furthermore, for each of the top 10 pairs ranked by ROS-DET, we attempted to identify a pathway, i.e. consecutive biological phenomena, being related with the corresponding two genes by checking the biological literature. In 8 out of the 10 pairs, we found two parallel pathways, one of the two genes being in each of the two pathways and two pathways coming to (or starting with) the same gene. This indicates that two parallel pathways would be cooperatively used under one experimental condition, corresponding to the positive correlation, and the two pathways might be alternatively used under the other condition, corresponding to the negative correlation. ROS-DET is available from http://www.bic.kyoto-u.ac.jp/pathway/kayano/ros-det.htm.en
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherOxford University Pressen
dc.rights© The Author(s) 2011. Published by Oxford University Press.en
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.en
dc.subject.meshData Interpretation, Statisticalen
dc.subject.meshGene Expression Profilingen
dc.subject.meshGene Expression Regulationen
dc.subject.meshROC Curveen
dc.titleROS-DET: robust detector of switching mechanisms in gene expression.en
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.ncidAA00760269-
dc.identifier.jtitleNucleic acids researchen
dc.identifier.volume39-
dc.identifier.issue11-
dc.relation.doi10.1093/nar/gkr130-
dc.textversionpublisher-
dc.identifier.artnume74-
dc.identifier.pmid21459849-
dcterms.accessRightsopen access-
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