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Proceedings Article

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

[+] Author Affiliations
Muhammed K. Turan, Eftal Sehirli, Abdullah Elen, Ismail R. Karas

Karabuk Univ. (Turkey)

Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 963110 (July 6, 2015); doi:10.1117/12.2197221
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From Conference Volume 9631

  • Seventh International Conference on Digital Image Processing (ICDIP 2015)
  • Charles M. Falco; Xudong Jiang
  • Los Angeles, United States | April 09, 2015

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. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Muhammed K. Turan ; Eftal Sehirli ; Abdullah Elen and Ismail R. 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 (July 6, 2015); doi:10.1117/12.2197221; http://dx.doi.org/10.1117/12.2197221


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