Jung Eun Shim , Won Suk Lee

The KIPS Transactions:PartD, Vol. 12, No. 5, pp. 719-728, Oct. 2005
10.3745/KIPSTD.2005.12.5.719,   PDF Download:

Abstract

2-dimensional electrophoresis(2DE) is a separation technique to identify proteins contained in a sample. However, the image is very sensitive to its experimental conditions as well as the quality of scanning. In order to adjust the possible variation of spots in a particular image, a user should manually annotate landmark spots on each gel image to analyze the spots of different images together. However, this operation is an error-prone and tedious job. This thesis develops an automated method of extracting the landmark spots of an image based on landmark profile. The landmark profile is created by clustering the previously identified landmarks of sample images of the same type. The profile contains the various properties of clusters identified for each landmark. When the landmarks of a new image need to be found, all the candidate spots of each landmark are first identified by examining the properties of its clusters. Subsequently, all the landmark spots of the new image are collectively found by the well-known optimization algorithm. The performance of this method is illustrated by various experiments on real 2DE images of mouse's brain-tissues.

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