A spot-matching framework for improving matching accuracy in protein 2-DE gel image analysis

Jung Eun Shim, Yanhua Jin, Won Suk Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The two-dimensional electrophoresis (2-DE) method is widely used in proteomics to separate thousands of proteins in a sample. Given a set of gel images of the same kind, a spot-matching operation identifies the spot of the same protein in each 2-DE gel image. However, since 2-DE gel images are very sensitive to various experimental conditions, spots observed in a 2-DE gel image involve inherent errors such as noises and irregular geometric distortions. Consequently, the accuracy of spot-matching is intensively influenced by these errors. This paper proposes a spot-matching framework to improve the accuracy of 2-DE gel image analysis. The framework includes an automatic landmark extraction module that uses a pattern model of positional and intensive distortions identified in the learning set of gel images. Subsequently, a probabilistic matching adjustment module is employed to produce more reliable spot-matching results based on the selected landmark spots in the first module. In order to confirm the synergy effects of integrating these two modules, the improved accuracy of the proposed framework is analyzed through various experiments on real 2-DE gel images of human liver tissue.

Original languageEnglish
Title of host publicationProceedings of IDEAS'08
Subtitle of host publicationInternational Database Engineering and Applications Symposium
Number of pages5
Publication statusPublished - 2008
EventInternational Database Engineering and Applications Symposium, IDEAS'08 - Coimbra, Portugal
Duration: 2008 Sept 102008 Sept 12

Publication series

NameACM International Conference Proceeding Series


OtherInternational Database Engineering and Applications Symposium, IDEAS'08

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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