Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorZineddin, B-
dc.contributor.authorWang, Z-
dc.contributor.authorShi, Y-
dc.contributor.authorLi, Y-
dc.contributor.authorDu, M-
dc.contributor.authorLiu, X-
dc.identifier.citationInternational Journal of Computational Biology and Drug Design, 3(2): 91 -111en_US
dc.descriptionThe official published version can be obtained from the link below.en_US
dc.description.abstractMicroarray has emerged as a powerful technology that enables biologists to study thousands of genes simultaneously, therefore, to obtain a better understanding of the gene interaction and regulation mechanisms. This paper is concerned with improving the processes involved in the analysis of microarray image data. The main focus is to clarify an image's feature space in an unsupervised manner. In this paper, the Image Transformation Engine (ITE), combined with different filters, is investigated. The proposed methods are applied to a set of real-world cDNA images. The MatCNN toolbox is used during the segmentation process. Quantitative comparisons between different filters are carried out. It is shown that the CLD filter is the best one to be applied with the ITE.en_US
dc.description.sponsorshipThis work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the National Science Foundation of China under Innovative Grant 70621001, Chinese Academy of Sciences under Innovative Group Overseas Partnership Grant, the BHP Billiton Cooperation of Australia Grant, the International Science and Technology Cooperation Project of China under Grant 2009DFA32050 and the Alexander von Humboldt Foundation of Germany.en_US
dc.subjectMicroarray image processingen_US
dc.subjectImage transformation engineen_US
dc.subjectMedian filteren_US
dc.subjectTop-hat filteren_US
dc.subjectLinear complex diffusionen_US
dc.subjectAdaptive segmentationen_US
dc.subjectComputational biologyen_US
dc.subjectcDNA imagesen_US
dc.subjectDNA microarraysen_US
dc.titleA multi-view approach to cDNA micro-array analysisen_US
dc.typeResearch Paperen_US
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext.pdf490.72 kBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.