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Bioinformatics Advance Access published online on December 6, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti816
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received November 1, 2004
Revised November 16, 2005
Accepted December 1, 2005

Article

Least Absolute Regression Network Analysis of the murine osteoblast differentiation network

E. P. van Someren 1 *, B. L. T. Vaes 2, W. T. Steegenga 3, A. M. Sijbers 4, K. J. Dechering 4, and M. J. T. Reinders 1

1 Department of Mediametics, Delft University of Technology, 2600 GA Delft, The Netherlands
2 Department of Applied Biology, University of Nijmegen, Nijmegen, The Netherlands
3 Department of Applied Biology, University of Nijmegen, Nijmegen, The Netherlands; Current affiliation: Nutrition, Metabolism and Genomics Group, Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands
4 N.V. Organon, Target Discovery Unit, Oss, The Netherlands

* To whom correspondence should be addressed.
E. P. van Someren, E-mail: E.P.vanSomeren{at}ewi.tudelft.nl


  Abstract

Motivation: We propose a reverse engineering scheme to discover genetic regulation from genome-wide transcription data that monitors the dynamic transcriptional response after a change in cellular environment. The interaction network is estimated by solving a linear model using simultaneous shrinking of the least absolute weights and the prediction error.

Results: The proposed scheme has been applied to the murine C2C12 cell-line stimulated to undergo osteoblast differentiation. Results show that our method discovers genetic interactions that display significant enrichment of co-citation in literature. More detailed study showed that the inferred network exhibits properties and hypotheses that are consistent with current biological knowledge.

Availability: Software is freely available for academic use as a Matlab package, called GENLAB: http://genlab.tudelft.nl/genlab.html.

Supplementary Information: Additional data, results and figures can be found at http://genlab.tudelft.nl/larna.html.


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