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Bioinformatics Advance Access published online on October 28, 2004
Bioinformatics, doi:10.1093/bioinformatics/bti093
Bioinformatics © Oxford University Press 2004; all rights reserved
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Received August 30, 2004
Revised October 1, 2004
Accepted October 5, 2004

Article

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

Ulrik de Lichtenberg 1, Lars Juhl Jensen 2, Anders Fausbøll 1, Thomas Skøt Jensen 1, Peer Bork 2, and Søren Brunak 1*

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

* To whom correspondence should be addressed.
Søren Brunak, E-mail: brunak{at}cbs.dtu.dk


  Abstract

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.


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