Abstract
Agarose or polyacrylamide gel electrophoresis is a common technique used to separate nucleic acids (DNA and RNA) according to their molecular weight, which generates images that can be analyzed automatically by a system. The separated DNA fragments of different molecular weights give a series of bands with positions in the gel image corresponding to their molecular weights. Automated image analysis of the gels removes much of the subjectivity of manual interpretation of band positions and sizes. In this paper, an automated system was designed for analyzing DNA bands using image and signal processing techniques. The proposed algorithm consists of four main steps: preprocessing to enhance the image, detecting lanes and bands, identifying band lengths and clustering; in which it can identify the similarities of the biological samples based on shared bands. The proposed technique eliminates defects due to noise and double bands in images. Ceylon Journal of Science (Bio. Sci.) 44 (1) : 45-54, 2015
Highlights
Electrophoresis is an electrochemical separation process of biological molecules such as DNA and proteins (Meyers et al, 1976)
The result of the electrophoresis can be presented as a gel image which contains several vertical lanes, each corresponding to a sample of analysis which has horizontal bands where each band is representing a mass of individual molecules of the same size (Mickel et al, 1977)
Analysis and interpretation of gel images followed by electrophoresis is cumbersome (Ho et al, 2004) especially when large number of samples are subjected to analysis (Brunello et al, 2001)
Summary
Electrophoresis is an electrochemical separation process of biological molecules such as DNA and proteins (Meyers et al, 1976). The result of the electrophoresis can be presented as a gel image which contains several vertical lanes, each corresponding to a sample of analysis which has horizontal bands where each band is representing a mass of individual molecules of the same size (Mickel et al, 1977). Contemporary algorithms for identifying, processing and analysis of gel images lack all the applications required for processing and these are not freely available for molecular biologists (Pavel and Vaslie, 2012). Further these may take a longer time for the process (Stathopoulou et al, 2006). The objective of this paper was to develop an automated system for agarose and polyacrylamide gel image analysis for research in molecular biology
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