Computational Strategies for Protein Quantitation in 2D Electrophoresis Gel Image Processor for Matlab

Computational Strategies for Protein Quantitation in 2D Electrophoresis Gel Image Processor for Matlab

In this paper, computational strategies are defined for protein quantisation by considering the shapes of the protein spots. The technique uses the clustering techniques like K-mean and fuzzy C-mean to distinguish between different types of protein spots and unwanted artifacts. The resulting techniq...

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Bibliographic Details
Published in:2007 Frontiers in the Convergence of Bioscience and Information Technologies pp. 129 - 134
Main Authors: Ijaz, U.Z., Chaudhary, S.U., Moon Sang Don, Kyung Youn Kim
Format: Conference Proceeding
Language:English
Published: IEEE 01-10-2007
Subjects:
Anodes
Biomedical engineering
Cathodes
Electrokinetics
Information technology
Pipelines
Protein engineering
Proteomics
Signal processing algorithms
Silver
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Summary:In this paper, computational strategies are defined for protein quantisation by considering the shapes of the protein spots. The technique uses the clustering techniques like K-mean and fuzzy C-mean to distinguish between different types of protein spots and unwanted artifacts. The resulting technique is used in 2D electrophoresis gel image processor for Matlab with other image manipulation techniquies on the experimental data to evaluate its performance.
ISBN:9780769529998
0769529992
DOI:10.1109/FBIT.2007.95