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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/4742

Title: Copasetic analysis: a framework for the blind analysis of microarray imagery
Authors: Fraser, K
O'Neill, P
Wang, Z
Liu, X
Keywords: Copasetic analysis
Blind analysis
Microarray image analysis
Bioinformatics
Domain expert knowledge
Processing techniques
Robustness
Noise
GenePix
Slide layout
Publication Date: 2004
Publisher: Institution of Engineering and Technology
Citation: System Biology, 1(1):190–196, Jun 2004
Abstract: From its conception, bioinformatics has been a multidisciplinary field which blends domain expert knowledge with new and existing processing techniques, all of which are focused on a common goal. Typically, these techniques have focused on the direct analysis of raw microarray image data. Unfortunately, this fails to utilise the image's full potential and in practice, this results in the lab technician having to guide the analysis algorithms. This paper presents a dynamic framework that aims to automate the process of microarray image analysis using a variety of techniques. An overview of the entire framework process is presented, the robustness of which is challenged throughout with a selection of real examples containing varying degrees of noise. The results show the potential of the proposed framework in its ability to determine slide layout accurately and perform analysis without prior structural knowledge. The algorithm achieves approximately, a 1 to 3 dB improved peak signal-to-noise ratio compared to conventional processing techniques like those implemented in GenePix® when used by a trained operator. As far as the authors are aware, this is the first time such a comprehensive framework concept has been directly applied to the area of microarray image analysis.
Description: The official published version can be found at the link below.
URI: http://bura.brunel.ac.uk/handle/2438/4742
DOI: http://dx.doi.org/10.1049/sb:20045002
ISSN: 1741-2471
Appears in Collections:Information Systems and Computing
School of Information Systems, Computing and Mathematics Research Papers

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