title: A multi-view approach to cDNA micro-array analysis.
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.
authors.affiliation: Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UK. Bachar.Zineddin@brunel.ac.uk
authors.forename: Bachar
authors.initials: B
authors.lastname: Zineddin
authors.forename: Zidong
authors.initials: Z
authors.lastname: Wang
authors.forename: Yong
authors.initials: Y
authors.lastname: Shi
authors.forename: Yurong
authors.initials: Y
authors.lastname: Li
authors.forename: Min
authors.initials: M
authors.lastname: Du
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D018076:DNA, Complementary / Q000378:metabolism; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*
chemical_list: D018076:DNA, Complementary