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Published online on May 1, 2003, 10.1073/pnas.0933416100

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Genetics
Reverse engineering gene networks: Integrating genetic perturbations with dynamical modeling

Jesper Tegnér *{dagger}{ddagger}§, M. K. Stephen Yeung *, Jeff Hasty *¶, and James J. Collins *

*Center for BioDynamics and Department of Biomedical Engineering, Boston University, Boston, MA 02215; {dagger}Division of Computational Biology, Department of Physics, Linköping University, S-581 83 Linköping, Sweden; {ddagger}Stockholm Bioinformatic Center, Stockholm Center for Physics, Astronomy, and Biotechnology, S-106 91 Stockholm, Sweden; and ¶Department of Bioengineering, University of California at San Diego, La Jolla, CA 92093-0412

Edited by Charles S. Peskin, New York University, New York, NY, and approved March 6, 2003 (received for review June 6, 2002)

While the fundamental building blocks of biology are being tabulated by the various genome projects, microarray technology is setting the stage for the task of deducing the connectivity of large-scale gene networks. We show how the perturbation of carefully chosen genes in a microarray experiment can be used in conjunction with a reverse engineering algorithm to reveal the architecture of an underlying gene regulatory network. Our iterative scheme identifies the network topology by analyzing the steady-state changes in gene expression resulting from the systematic perturbation of a particular node in the network. We highlight the validity of our reverse engineering approach through the successful deduction of the topology of a linear in numero gene network and a recently reported model for the segmentation polarity network in Drosophila melanogaster. Our method may prove useful in identifying and validating specific drug targets and in deconvolving the effects of chemical compounds.

§To whom correspondence should be addressed.

E-mail: jespert{at}ifm.liu.se.

www.pnas.org/cgi/doi/10.1073/pnas.0933416100
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