Hierarchical Clustering Analysis from Genomic Dataset

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2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'05)

Compi?gne University of Technology, France

September 19-September 22

ISBN: 0-7695-2416-8

	ASCII Text	x
	Wei Yin, Qing Yang, Shaoyuan Yao, Yong Shi, "Hierarchical Clustering Analysis from Genomic Dataset," Intelligent Agent Technology, IEEE / WIC / ACM International Conference on, pp. 759-762, 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'05), 2005.

	BibTex	x
	@article{ 10.1109/IAT.2005.81, author = {Wei Yin and Qing Yang and Shaoyuan Yao and Yong Shi}, title = {Hierarchical Clustering Analysis from Genomic Dataset}, journal ={Intelligent Agent Technology, IEEE / WIC / ACM International Conference on}, volume = {0}, year = {2005}, isbn = {0-7695-2416-8}, pages = {759-762}, doi = {http://doi.ieeecomputersociety.org/10.1109/IAT.2005.81}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Intelligent Agent Technology, IEEE / WIC / ACM International Conference on TI - Hierarchical Clustering Analysis from Genomic Dataset SN - 0-7695-2416-8 SP759 EP762 A1 - Wei Yin, A1 - Qing Yang, A1 - Shaoyuan Yao, A1 - Yong Shi, PY - 2005 KW - null VL - 0 JA - Intelligent Agent Technology, IEEE / WIC / ACM International Conference on ER -

Wei Yin, CAS Research Center on Data Technology & Knowledge Economy and Graduate University of Chinese Academy of Sciences, Beijing, 100080, China

Qing Yang, Institute of Software, Chinese Academy of Science, Beijing, 100080, China

Shaoyuan Yao, State Key Laboratory of Reproductive Biology, Chinese Academy of Science, Beijing,

Yong Shi, CAS Research Center on Data Technology & Knowledge Economy and Graduate University of Chinese Academy of Sciences, Beijing, 100080, China

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IAT.2005.81

In this paper, we use the method proposed by Eisen to analyze the genomic data collected from the State Key Laboratory of Reproductive Biology, Chinese Academy of Sciences. The analysis shows that the clustering methods effectively group genes of similar functions.1

Citation:

Wei Yin, Qing Yang, Shaoyuan Yao, Yong Shi, "Hierarchical Clustering Analysis from Genomic Dataset," iat, pp.759-762, 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'05), 2005

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