Application of Classification Association Rule Mining for Mammalian Mesenchymal Stem Cell Differentiation

Authors:
Weiqi Wang;Yanbo J. Wang;René Bañares-Alcántara;Zhanfeng Cui;Frans Coenen
Affiliations:
Department of Engineering Science, University of Oxford, UK OX1 3PJ;Information Management Center, China Minsheng Banking Corp., Ltd., Beijing, China 100873;Department of Engineering Science, University of Oxford, UK OX1 3PJ;Department of Engineering Science, University of Oxford, UK OX1 3PJ;Department of Computer Science, University of Liverpool, Liverpool, UK L69 3BX
Venue:
ICDM '09 Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects
Year:
2009

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Abstract

In this paper, data mining is used to analyze the differentiation of mammalian Mesenchymal Stem Cells (MSCs). A database comprising the key parameters which, we believe, influence the destiny of mammalian MSCs has been constructed. This paper introduces Classification Association Rule Mining (CARM) as a data mining technique in the domain of tissue engineering and initiates a new promising research field. The experimental results show that the proposed approach performs well with respect to the accuracy of (classification) prediction. Moreover, it was found that some rules mined from the constructed MSC database are meaningful and useful.