Title: Temporal clustering of gene expression patterns using short-time segments

Authors: Nguyen Nguyen; Ying Ann Chiao; Yufei Huang; Shou-Jiang Gao; Merry Lindsey; Yidong Chen; Yufang Jin

Addresses: Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX 78249, USA ' Health Science Center at San Antonio, Department of Biochemistry, University of Texas, San Antonio, TX 78229, USA ' Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX 78249, USA ' Greehey Children's Cancer Research Institute, University of Texas, Health Science Center at San Antonio, San Antonio, TX 78229, USA ' Department of Medicine, University of Texas, Health Science Center at San Antonio, San Antonio, TX 78229, USA ' Department of Epidemiology and Biostatistics, University of Texas, Health Science Center at San Antonio, San Antonio, TX 78229, USA ' Department of Electrial and Computer Engineering, One UTSA Circle San Antonio, TX 78249, USA

Abstract: Temporal clustering of time series data is a powerful tool to delaminate the dynamics of transcription and interactions among genes on a large scale. Different algorithms have been proposed to organise experimental data with meaningful biological clusters; however, these approaches often fail to generate well-defined temporal clusters, especially when genes exert their functions or response to stimuli coordinately only in a short period of time span. In this study, we proposed an algorithm using sliding windows to identify different temporal patterns based on fold changes of gene expressions. The algorithm was applied to simulated data and real experimental data. Furthermore, a comparison study has been carried out with the clusters obtained from commercial software packages. The identified clusters using our algorithm demonstrated better temporal matching and consistency.

Keywords: short-time segments; gene expression patterns; temporal clustering; sliding windows; biological clusters; temporal matching; consistency.

DOI: 10.1504/IJFIPM.2012.050419

International Journal of Functional Informatics and Personalised Medicine, 2012 Vol.4 No.1, pp.32 - 46

Received: 21 May 2011
Accepted: 12 Jun 2011
Published online: 20 Nov 2012 *

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