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Bioinformatics Advance Access originally published online on October 28, 2004
Bioinformatics 2005 21(7):1164-1171; doi:10.1093/bioinformatics/bti093
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© The Author 2004. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Comparison of computational methods for the identification of cell cycle-regulated genes

Ulrik de Lichtenberg 1,{dagger}, Lars Juhl Jensen 2,{dagger}, Anders Fausbøll 1, Thomas S. Jensen 1, Peer Bork 2 and Søren Brunak 1,*

1Center for Biological Sequence Analysis, Technical University of Denmark DK-2800 Lyngby, Denmark
2European Molecular Biology Laboratory D-69117 Heidelberg, Germany

*To whom correspondence should be addressed.

Motivation: DNA microarrays have been used extensively to study the cell cycle transcription programme in a number of model organisms. The Saccharomyces cerevisiae data in particular have been subjected to a wide range of bioinformatics analysis methods, aimed at identifying the correct and complete set of periodically expressed genes.

Results: Here, we provide the first thorough benchmark of such methods, surprisingly revealing that most new and more mathematically advanced methods actually perform worse than the analysis published with the original microarray data sets. We show that this loss of accuracy specifically affects methods that only model the shape of the expression profile without taking into account the magnitude of regulation. We present a simple permutation-based method that performs better than most existing methods.

Supplementary information: Results and benchmark sets are available at http://www.cbs.dtu.dk/cellcycle

Contact: brunak{at}cbs.dtu.dk


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