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Pradeepa, R.
- Layered Approach for Predicting Protein Subcellular Localization in Yeast Microarray Data
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Authors
A. Kumaravel
1,
R. Pradeepa
2
Affiliations
1 Department of Computer Science and Engineering, Bharath University, Selaiyur, Chennai-600073, IN
2 Department of Computer Science and Engineering, Bharath University, Selaiyur, Chennai - 600073
1 Department of Computer Science and Engineering, Bharath University, Selaiyur, Chennai-600073, IN
2 Department of Computer Science and Engineering, Bharath University, Selaiyur, Chennai - 600073
Source
Indian Journal of Science and Technology, Vol 6, No S5 (2013), Pagination: 4567-4571Abstract
Subcellular localization is a well-designed representation of proteins. We need a fully automatic and reliable prediction system for protein subcellular localization, especially for the analysis of large-scale of yeast microarray data. In this paper we consider the dataset with multi classes and propose the classification for each location of protein subcellular in a separate layer. In this work, a multi-classification approach for subcellular localization is designed and developed to achieve high efficiency and improve the prediction and classification accuracy. The rule based Ripper method has been found to predict the subcellular localization of proteins from their protein microarray data, compared to other classifiers.Keywords
Data Mining, Microarray, Classification, Layered Approach, Protein Subcellular LocalizationFull Text
References
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