Shim Jung Eun, Lee Won Suk
Department of Computer Science, Yonsei University, 134 Shinchon-dong Seodaemun-gu, Seoul 120-749, Korea.
Artif Intell Med. 2005 Sep-Oct;35(1-2):157-70. doi: 10.1016/j.artmed.2005.07.002.
Two-dimensional electrophoresis (2DE) is a separation technique that can identify target proteins existing in a tissue. Its result is represented by a gel image that displays an individual protein in a tissue as a spot. However, because the technique suffers from low reproducibility, a user should manually annotate landmark spots on each gel image to analyze the spots of different images together. This operation is an error-prone and tedious job. For this reason, this paper proposes a method of extracting landmark spots automatically by using a data mining technique.
A landmark profile which summarizes the characteristics of landmark spots in a set of training gel images of the same tissue is generated by extracting the common properties of the landmark spots. On the basis of the landmark profile, candidate landmark spots in a new gel image of the same tissue are identified, and final landmark spots are determined by the well-known A* search algorithm.
The performance of the proposed method is analyzed through a series of experiments in order to identify its various characteristics.
二维电泳（2DE）是一种可识别组织中存在的目标蛋白质的分离技术。其结果由凝胶图像表示，该图像将组织中的单个蛋白质显示为一个斑点。然而，由于该技术的重现性较低，用户需要在每个凝胶图像上手动标注地标斑点，以便一起分析不同图像的斑点。此操作容易出错且繁琐。因此，本文提出一种利用数据挖掘技术自动提取地标斑点的方法。
通过提取地标斑点的共同属性，生成一个地标轮廓，该轮廓总结了同一组织的一组训练凝胶图像中地标斑点的特征。基于该地标轮廓，识别同一组织新凝胶图像中的候选地标斑点，并通过著名的A*搜索算法确定最终的地标斑点。
通过一系列实验分析了所提方法的性能，以确定其各种特性。
