Neighborhood matrix: A new idea in matching of two dimensional gel images

Automated data analysis and pattern recognition techniques are the requirements of biological and proteomics research studies. The analysis of proteins consists of some stages among which the analysis of two dimensional electrophoresis (2-DE) images is crucial. The aim of image capturing is to generate a Photostat that can be used in future works such as image comparison. The researchers introduced a new method for matching two 2-DE gel images. In this method, a neighborhood circular region is defined to obtain information about spots’ neighbors. In the present paper, the information obtained by this region is reordered into a matrix as a descriptor of the neighbors of each spot. The matrix is then used in matching the spots between two images. All conducted tests to evaluate the method’s performance showed the power of the method in spot matching, even when the number of candidate matching spots in the second images increased. The proposed method provides a robust automatic comparison idea in gel images matching. Despite its low speed, its accuracy is excellent. The Novelty of the present study is the use of matrices as neighborhood descriptor. This idea is applicable in any other similar domain.