Abstract
Images obtained through the gel electrophoresis technique contain important genetic information. However, due to degradations and abnormalities from which these images suffer, extracting this information can be a tedious task and may lead to reproducibility issues. Image processing techniques that are commonly used to analyze gel electrophoresis images require three main steps: band detection, band matching, and quantification. Although several techniques were proposed to automate all steps fully, gel image analysis still requires researchers to extract information manually. This type of extraction is time consuming and subject to human errors. This paper proposes a fully automated system to analyze the gel electrophoresis images. This system involves four main steps: lane separation, lane segmentation, band detection, and data quantification.
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Labyed, Y., Kaabouch, N., Schultz, R.R., Singh, B.B., Milavetz, B. (2010). An Improved 1-D Gel Electrophoresis Image Analysis System. In: Arabnia, H. (eds) Advances in Computational Biology. Advances in Experimental Medicine and Biology, vol 680. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-5913-3_67
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DOI: https://doi.org/10.1007/978-1-4419-5913-3_67
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