Structural Matching of 2D Electrophoresis Gels using Graph Models

Abstract

2D electrophoresis is a well known method for protein separation which is extremely useful in the field of proteomics. Each spot in the image represents a protein accumulation and the goal is to perform a differential analysis between pairs of images to study changes in protein content. It is thus necessary to register two images by finding spot correspondences. Although it may seem a simple task, generally, the manual processing of this kind of images is very cumbersome. The complete task of individual spot matching and gel registration is a complex and time consuming process when strong variations between corresponding sets of spots are expected. Besides, because an one-to-one mapping is expected between the two images, missing spots there may exist on both images (i.e. spots without correspondence). In order to solve this problem, this paper proposes a new distance together with a correspondence estimation algorithm based on graph matching which takes into account the structural information between the detected spots. Each image is represented by a graph and the task is to find an isomorphism between subgraphs. Successful experimental results using real data are presented, including a comparative performance evaluation.