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Gene Selection and Classification Rule Generation for Microarray Dataset

  • Soumen Kumar Pati
  • Asit Kumar Das
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 178)

Abstract

Microarray is a useful technique for measuring expression data of thousands or more of genes simultaneously. One of challenges in classification of cancer using high-dimensional gene expression data is to select a minimal number of relevant genes which can maximize classification accuracy. Because of the distinct characteristics inherent to specific cancerous gene expression profiles, developing flexible and robust gene identification methods is extremely fundamental. Many gene selection methods as well as their corresponding classifiers have been proposed. In the proposed method, a single gene with high class-discrimination capability is selected and classification rules are generated for cancer based on gene expression profiles.

Keywords

Microarray cancer data K-means algorithm Gene selection Classification Rule Cancer sample identification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Computer Science/Information TechnologySt. Thomas‘ College of Engineering and TechnologyKolkataIndia
  2. 2.Department of Computer Science and TechnologyBengal Engineering and Science UniversityHowrahIndia

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