Title: A multi-view approach to cDNA micro-array analysis

Authors: Bachar Zineddin, Zidong Wang, Yong Shi, Yurong Li, Min Du, Xiaohui Liu

Addresses: Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UB8 3PH, UK. ' Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UB8 3PH, UK. ' CAS Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100080, China; College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE 68182, USA. ' Department of Electrical Engineering, Fuzhou University, Fuzhou 350002, China. ' Department of Electrical Engineering, Fuzhou University, Fuzhou 350002, China. ' Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UB8 3PH, UK

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.

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.

DOI: 10.1504/IJCBDD.2010.035237

International Journal of Computational Biology and Drug Design, 2010 Vol.3 No.2, pp.91 - 111

Available online: 16 Sep 2010 *

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