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An interactive approach to mining gene expression data

Publication ,  Journal Article
Jiang, D; Pei, J; Zhang, A
Published in: IEEE Transactions on Knowledge and Data Engineering
October 1, 2005

Effective identification of coexpressed genes and coherent patterns in gene expression data is an important task in bioinformatics research and biomedical applications. Several clustering methods have recently been proposed to identify coexpressed genes that share similar coherent patterns. However, there is no objective standard for groups of coexpressed genes. The interpretation of co-expression heavily depends on domain knowledge. Furthermore, groups of coexpressed genes in gene expression data are often highly connected through a large number of "intermediate" genes. There may be no clear boundaries to separate clusters. Clustering gene expression data also faces the challenges of satisfying biological domain requirements and addressing the high connectivity of the data sets. In this paper, we propose an interactive framework for exploring coherent patterns in gene expression data. A novel coherent pattern index is proposed to give users highly confident indications of the existence of coherent patterns. To derive a coherent pattern index and facilitate clustering, we devise an attraction tree structure that summarizes the coherence information among genes in the data set. We present efficient and scalable algorithms for constructing attraction trees and coherent pattern indices from gene expression data sets. Our experimental results show that our approach is effective in mining gene expression data and is scalable for mining large data sets. © 2005 IEEE.

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Published In

IEEE Transactions on Knowledge and Data Engineering

DOI

ISSN

1041-4347

Publication Date

October 1, 2005

Volume

17

Issue

10

Start / End Page

1363 / 1378

Related Subject Headings

  • Information Systems
  • 46 Information and computing sciences
  • 08 Information and Computing Sciences
 

Citation

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Jiang, D., Pei, J., & Zhang, A. (2005). An interactive approach to mining gene expression data. IEEE Transactions on Knowledge and Data Engineering, 17(10), 1363–1378. https://doi.org/10.1109/TKDE.2005.159
Jiang, D., J. Pei, and A. Zhang. “An interactive approach to mining gene expression data.” IEEE Transactions on Knowledge and Data Engineering 17, no. 10 (October 1, 2005): 1363–78. https://doi.org/10.1109/TKDE.2005.159.
Jiang D, Pei J, Zhang A. An interactive approach to mining gene expression data. IEEE Transactions on Knowledge and Data Engineering. 2005 Oct 1;17(10):1363–78.
Jiang, D., et al. “An interactive approach to mining gene expression data.” IEEE Transactions on Knowledge and Data Engineering, vol. 17, no. 10, Oct. 2005, pp. 1363–78. Scopus, doi:10.1109/TKDE.2005.159.
Jiang D, Pei J, Zhang A. An interactive approach to mining gene expression data. IEEE Transactions on Knowledge and Data Engineering. 2005 Oct 1;17(10):1363–1378.

Published In

IEEE Transactions on Knowledge and Data Engineering

DOI

ISSN

1041-4347

Publication Date

October 1, 2005

Volume

17

Issue

10

Start / End Page

1363 / 1378

Related Subject Headings

  • Information Systems
  • 46 Information and computing sciences
  • 08 Information and Computing Sciences