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Bioinformatics Advance Access published online on January 24, 2006

Bioinformatics, doi:10.1093/bioinformatics/btl017
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received December 4, 2005
Revised January 12, 2006
Accepted January 13, 2006

Article

Polynomial model approach for resynchronization analysis of cell-cycle gene expression data

Peng Qiu 1 *, Z. Jane Wang 2, and K. J. Ray Liu 1

1 Department of Electrical and Computer Engineering, University of Maryland, College Park, USA
2 Department of Electrical and Computer Engineering, University of British Columbia, Canada

* To whom correspondence should be addressed.
Peng Qiu, E-mail: qiupeng{at}umd.edu


   Abstract

Motivation: Identification of genes expressed in a cell-cycle-specific periodical manner is of great interest to understand cyclic systems which play a critical role in many biological processes. However, identification of cell-cycle regulated genes by raw microarray gene expression data directly is complicated by the factor of synchronization loss, thus remains a challenging problem. Decomposing the expression measurements and extracting synchronized expression will allow to better represent the single-cell behavior and improve the accuracy in identifying periodically expressed genes.

Results: In this paper, we propose a resynchronization-based algorithm for identifying cell-cycle-related genes. We introduce a synchronization loss model by modeling the gene expression measurements as a superposition of different cell populations growing at different rates. The underlying expression profile is then reconstructed through resynchronization and is further fitted to the measurements in order to identify periodically expressed genes. Results from both simulations and real mircorarray data show that the proposed scheme is promising for identifying cyclic genes and revealing underlying gene expression profiles.

Availability: Contact the authors.


Associate Editor: David Rocke
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