Given a number of 2-DE gel images of the same kind, identifying the spot of each image for the same protein is an important task to monitor the expression level change of the protein. For this purpose, the gel-based two-dimensional electrophoresis method (2-DE) is widely used since it separates thousands of proteins in a sample cost-effectively. However, this approach suffers from inherent noises and irregular geometric distortions of spots observed in a 2-DE gel image. This paper proposes a probability-based error filtering method that can find more reliable spot-matching results, so that the accuracy of protein expression analysis can be improved. The performance of the proposed method is analyzed by various experiments on real 2-DE gel images of human liver tissues.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence