Learning the tree of phenotypes using genomic data and VISDA

Yuanjian Feng; Zuyi Wang; Yitan Zhu; Jianhua Xuan; David J. Miller; Robert Clarke; Eric P. Hoffman; Yue Wang

doi:10.1109/BIBE.2006.253330

Learning the tree of phenotypes using genomic data and VISDA

Yuanjian Feng, Zuyi Wang, Yitan Zhu, Jianhua Xuan, David J. Miller, Robert Clarke, Eric P. Hoffman, Yue Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Though supervised and unsupervised analyses of genomic data have been intensively studied in recent years, little effort has been made to discover the structural information contained in the data. In this work, we propose a stability analysis guided supervised clustering and visualization method aiming to discover the hierarchical structure in gene expression data, which we call the "tree of phenotypes". We applied the method on two multiclass gene expression microarray data sets and presented the biological plausibility of the learned trees. We also tested the multiclass classifiers built on the learned trees and demonstrated their good classification performance.

Original language	English (US)
Title of host publication	Proceedings - Sixth IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006
Pages	165-170
Number of pages	6
DOIs	https://doi.org/10.1109/BIBE.2006.253330
State	Published - 2006
Externally published	Yes
Event	6th IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006 - Arlington, VA, United States Duration: Oct 16 2006 → Oct 18 2006

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Name	Proceedings - Sixth IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006

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Other	6th IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006
Country/Territory	United States
City	Arlington, VA
Period	10/16/06 → 10/18/06

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Feng, Y., Wang, Z., Zhu, Y., Xuan, J., Miller, D. J., Clarke, R., Hoffman, E. P., & Wang, Y. (2006). Learning the tree of phenotypes using genomic data and VISDA. In Proceedings - Sixth IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006 (pp. 165-170). Article 4019655 (Proceedings - Sixth IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006). https://doi.org/10.1109/BIBE.2006.253330

Learning the tree of phenotypes using genomic data and VISDA. / Feng, Yuanjian; Wang, Zuyi; Zhu, Yitan et al.
Proceedings - Sixth IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006. 2006. p. 165-170 4019655 (Proceedings - Sixth IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Feng, Y, Wang, Z, Zhu, Y, Xuan, J, Miller, DJ, Clarke, R, Hoffman, EP & Wang, Y 2006, Learning the tree of phenotypes using genomic data and VISDA. in Proceedings - Sixth IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006., 4019655, Proceedings - Sixth IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006, pp. 165-170, 6th IEEE Symposium on BioInformatics and BioEngineering, BIBE 2006, Arlington, VA, United States, 10/16/06. https://doi.org/10.1109/BIBE.2006.253330

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AU - Clarke, Robert

AU - Hoffman, Eric P.

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AB - Though supervised and unsupervised analyses of genomic data have been intensively studied in recent years, little effort has been made to discover the structural information contained in the data. In this work, we propose a stability analysis guided supervised clustering and visualization method aiming to discover the hierarchical structure in gene expression data, which we call the "tree of phenotypes". We applied the method on two multiclass gene expression microarray data sets and presented the biological plausibility of the learned trees. We also tested the multiclass classifiers built on the learned trees and demonstrated their good classification performance.

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Learning the tree of phenotypes using genomic data and VISDA

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