A landmark extraction method for protein 2DE gel images based on multi-dimensional clustering

Objective: 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. Method and material: 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. Result and conclusions: The performance of the proposed method is analyzed through a series of experiments in order to identify its various characteristics.