Identification of column edges of DNA fragments by using K-means clustering and mean algorithm on lane histograms of DNA agarose gel electrophoresis images

Muhammed Kamil Turan; Eftal Sehirli; Abdullah Elen; Ismail Rakip Karas

doi:10.1117/12.2197221

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6 July 2015 Identification of column edges of DNA fragments by using K-means clustering and mean algorithm on lane histograms of DNA agarose gel electrophoresis images

Muhammed Kamil Turan, Eftal Sehirli, Abdullah Elen, Ismail Rakip Karas

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Proceedings Volume 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015); 963110 (2015) https://doi.org/10.1117/12.2197221
Event: Seventh International Conference on Digital Image Processing (ICDIP15), 2015, Los Angeles, United States

Abstract

Gel electrophoresis (GE) is one of the most used method to separate DNA, RNA, protein molecules according to size, weight and quantity parameters in many areas such as genetics, molecular biology, biochemistry, microbiology. The main way to separate each molecule is to find borders of each molecule fragment. This paper presents a software application that show columns edges of DNA fragments in 3 steps. In the first step the application obtains lane histograms of agarose gel electrophoresis images by doing projection based on x-axis. In the second step, it utilizes k-means clustering algorithm to classify point values of lane histogram such as left side values, right side values and undesired values. In the third step, column edges of DNA fragments is shown by using mean algorithm and mathematical processes to separate DNA fragments from the background in a fully automated way. In addition to this, the application presents locations of DNA fragments and how many DNA fragments exist on images captured by a scientific camera.

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Muhammed Kamil Turan, Eftal Sehirli, Abdullah Elen, and Ismail Rakip Karas "Identification of column edges of DNA fragments by using K-means clustering and mean algorithm on lane histograms of DNA agarose gel electrophoresis images ", Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 963110 (6 July 2015); https://doi.org/10.1117/12.2197221

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