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International Symposium on Bioinformatics Research and Applications

ISBRA 2016: Bioinformatics Research and Applications pp 284–294Cite as

Improved Detection of 2D Gel Electrophoresis Spots by Using Gaussian Mixture Model

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 9683))

Abstract

2D gel electrophoresis is the most commonly used method in biomedicine to separate even thousands of proteins in a complex sample. Although the technique is quite known, there is still a need to find an efficient and automatic method for detection of protein spots on gel images. In this paper a mixture of 2D normal distribution functions is introduced to improve the efficiency of spot detection using the existing software. A comparison of methods is based on simulated datasets with known true positions of spots. Fitting a mixture of components to the gel image allows for achieving higher sensitivity in detecting spots, better overall performance of the spot detection and more accurate estimates of spot centers. Efficient implementation of the algorithm enables parallel computing capabilities that significantly decrease the computational time.

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Acknowledgments

This work was financially supported by the internal grant for young researchers from Silesian University of Technology number BKM/514/RAu1/2015/34. All calculations were carried out using GeCONiI infrastructure funded by the project number POIG.02.03.01-24-099/13.

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Authors and Affiliations

  1. Data Mining Group, Institute of Automatic Control, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Michal Marczyk

Authors
  1. Michal Marczyk
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Correspondence to Michal Marczyk .

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Editors and Affiliations

  1. Dept. of Computer Science, Georgia State University, Atlanta, Georgia, USA

    Anu Bourgeois

  2. Centre for Disease Control & Prevention, Atlanta, Georgia, USA

    Pavel Skums

  3. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Xiang Wan

  4. Georgia State University, Atlanta, Georgia, USA

    Alex Zelikovsky

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© 2016 Springer International Publishing Switzerland

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Marczyk, M. (2016). Improved Detection of 2D Gel Electrophoresis Spots by Using Gaussian Mixture Model. In: Bourgeois, A., Skums, P., Wan, X., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2016. Lecture Notes in Computer Science(), vol 9683. Springer, Cham. https://doi.org/10.1007/978-3-319-38782-6_24

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  • DOI: https://doi.org/10.1007/978-3-319-38782-6_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-38781-9

  • Online ISBN: 978-3-319-38782-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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