Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/3275
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dc.contributor.authorFraser, K-
dc.contributor.authorWang, Z-
dc.contributor.authorLi, Y-
dc.contributor.authorKellam, P-
dc.contributor.authorLiu, X-
dc.coverage.spatial8en
dc.date.accessioned2009-05-02T10:55:29Z-
dc.date.available2009-05-02T10:55:29Z-
dc.date.issued2008-
dc.identifier.citationPattern Recognition Letters. 29(16): 2129-2136en
dc.identifier.urihttp://www.elsevier.com/wps/find/ journaldescription.cws_home/505619/description#descriptionen
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/3275-
dc.description.abstractMicroarrays produce high-resolution image data that are, unfortunately, permeated with a great deal of “noise” that must be removed for precision purposes. This paper presents a technique for such a removal process. On completion of this non-trivial task, a new surface (devoid of gene spots) is subtracted from the original to render more precise gene expressions. The graph-cutting technique as implemented has the benefits that only the most appropriate pixels are replaced and these replacements are replicates rather than estimates. This means the influence of outliers and other artifacts are handled more appropriately (than in previous methods) as well as the variability of the final gene expressions being considerably reduced. Experiments are carried out to test the technique against commercial and previously researched reconstruction methods. Final results show that the graph-cutting inspired identification mechanism has a positive significant impact on reconstruction accuracy.en
dc.format.extent909297 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherElsevier-
dc.subjectcDNA; Two channel; Microarrays; Background reconstruction; Graph-edge cutsen
dc.titleCan graph-cutting improve microarray gene expression reconstructions?en
dc.typeResearch Paperen
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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