Abstract
Matching spots between two-dimensional electrophoresis (2-DE) images is a bottleneck in the automation of proteome analysis. Because the matching problem is an NP-hard problem, the solution is usually a heuristic approach or a neural network method. So a Hopfield neural network approach is applied to solve this problem. An energy function is designed to represent the similarity of spots together with its neighbor spots. Experiment showed that Hopfield neural network with appropriate energy function and dynamics could solve the matching problem of spots in 2-DE images. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Hwang, Y. S., Park, H., & Chung, Y. (2005). Pairwise matching of spots in 2-DE images using Hopfield network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3558 LNAI, pp. 264–271). Springer Verlag. https://doi.org/10.1007/11526018_26
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