Temporal clustering of gene expression patterns using short-time segments

Nguyen Nguyen, Yufang Jin, Yufei Huang, Ying Ann Chiao, Shou Jiang Gao, Merry Lindsey, Yidong Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

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 organize 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 stimulation coordinately only in a short time span. In this study, we propose an algorithm using sliding windows to identify different temporal patterns based on fold changes of gene expression. 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.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010
Pages173-178
Number of pages6
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010 - HongKong, China
Duration: Dec 18 2010Dec 21 2010

Publication series

Name2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010

Other

Other2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010
CountryChina
CityHongKong
Period12/18/1012/21/10

Keywords

  • Gene expression patterns
  • Short-time segments
  • Sliding window
  • Temporal clustering

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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