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http://dx.doi.org/10.3745/KIPSTB.2006.13B.3.323

Gel Image Matching Using Hopfield Neural Network  

Ankhbayar Yukhuu (선문대학교 컴퓨터정보학부)
Hwang Suk-Hyung (선문대학교 컴퓨터정보학부)
Hwang Young-Sup (선문대학교 컴퓨터정보학부)
Publication Information
The KIPS Transactions:PartB / v.13B, no.3, 2006 , pp. 323-328 More about this Journal
Abstract
Proteins in a cell appear as spots in a two dimensional gel image which is used in protein analysis. The spots from the same protein are in near position when comparing two gel images. Finding out the different proteins between a normal tissue and a cancer one is important information in drug development. Automatic matching of gel images is difficult because they are made from biological experimental processes. This matching problem is known to be NP-hard. Neural networks are usually used to solve such NP-hard problems. Hopfield neural network is selected since it is appropriate to solve the gel matching. An energy function with location and distance parameters is defined. The two spots which make the energy function minimum are matching spots and they came from the same protein. The energy function is designed to reflect the topology of spots by examining not only the given spot but also neighborhood spots.
Keywords
Protein; Gel Image; Hopfield Neural Network; Spot Matching;
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