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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/4733

Title: A multi-view approach to cDNA micro-array analysis
Authors: Zineddin, B
Wang, Z
Shi, Y
Li, Y
Du, M
Liu, X
Keywords: Microarray image processing
ITE
Image transformation engine
Median filter
Top-hat filter
Linear complex diffusion
Adaptive segmentation
Computational biology
cDNA images
Filtering
DNA microarrays
Publication Date: 2010
Publisher: Inderscience
Citation: International Journal of Computational Biology and Drug Design, 3(2): 91 -111
Abstract: Microarray 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.
Description: The official published version can be obtained from the link below.
Sponsorship: This 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.
URI: http://bura.brunel.ac.uk/handle/2438/4733
DOI: http://dx.doi.org/10.1504/IJCBDD.2010.035237
ISSN: 1756-0756
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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