• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2013, Volume: 6, Issue: Supplementary 5, Pages: 1-5

Original Article

Layered Approach for Predicting Protein Subcellular Localization in Yeast Microarray Data


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 Localization.


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