期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2011
卷号：4
期号：1
出版社：SERSC
摘要：Two-dimensional polyacrylamide gel electrophoresis of proteins is a robust and reproducible technique. It is the most widely used separation tool in proteomics. Current efforts in the field are directed at development of tools for expanding the range of proteins accessible with two-dimensional gels. Proteomics was built around the two-dimensional gel. The idea that multiple proteins can be analyzed in parallel grew from two-dimensional gel maps. Proteomics researchers needed to identify interested protein spots by examining the gel. This is time consuming, labor extensive and error prone. It is desired that the computer can analyze the proteins automatically by first detecting then quantifying the protein spots in the 2-D gel images. In our previous work, we presented a new technique for segmentation of 2-D gel images using the fuzzy c-means algorithm using the notion of fuzzy relations. In this paper, we will describe the new relational fuzzy c-means algorithm (RFCM) and use it for automatic protein spots quantification. We will also use two methods to evaluate its performance: the unsupervised evaluation method and comparison with the expert spots quantification.
关键词：2D gel images; Protein Spot Detection; Protein Spot Quantification;Fuzzy c-means algorithm; Fuzzy relations; and Computer vision.
