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Journal of Information Science and Engineering, Vol.19 No.6, pp.909-921 (November 2003)


Mining Correlations of Human Gene Expression from Digital Gene Expression Profiles

Jorng-Tzong Horng1,2,*, Hsien-Da Huang2, Kuo-Yen Tseng2,
Tsung-Shan Tsou3, Baw-Jhiune Liu4 and Cheng-Yan Kao5
1Department of Life Science
2Department of Computer Science and Information Engineering
3Institute of Statistics
National Central University
*E-mail: horng@db.csie.ncu.edu.tw
4Department of Computer Science and Engineering
Yuan-Ze University
Chungli, 320 Taiwan
5Department of Computer Science and Information Engineering
National Taiwan University
Taipei, 106 Taiwan

The study addressed here aimed to analyze a large number of human genome transcripts from diverse tissues and to discover genes that with similar expression profiles in different human tissues. These genes may be of potential biological or pharmaceutical relevance. We propose an approach to discover the correlations of tissue gene expression by analyzing digital gene expression profiles of different human tissues. A simple statistical test was used to correlate genes having similar expression profiles. We used the information of tissue gene expression to discover the correlations of expressed genes. The correlations of gene expression revealed that such genes were specifically expressed in particular tissues with similar expression profiles and could be used to identify the relationships of the genes that be co-regulated, involved in the same biochemical pathway and signal transduction process.

Keywords: gene expression, data mining, EST, SAGE, UniGene

Full Text () Retrieve PDF document (200311_01.pdf)

Received November 1, 2002; accepted June 5, 2003.
Communicated by Chuen-Tsai Sun.