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Bioinformatics Advance Access published online on July 1, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp411
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© The Author (2009). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Determining noisy attractors of delayed stochastic Gene Regulatory Networks from multiple data sources

Xiaofeng Dai 1, Olli Yli-Harja 1,2 and Andre S. Ribeiro 1

1Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, Finland.
2Institute for Systems Biology, Seattle, WA, USA.

To whom correspondence should be addressed. Dr. Andre S. Ribeiro, E-mail: andre.sanchesribeiro{at}tut.fi


  Abstract

Motivation: Gene regulatory networks (GRN) are stochastic, thus, do not have attractors, but can remain in confined regions of the state space, the ‘noisy attractors’, which define the cell type and phenotype.

Results: We propose a gamma-bernoulli mixture model clustering algorithm ({Gamma}BMM), tailored for quantizing states from gamma and bernoulli distributed data, to determine the noisy attractors of stochastic GRN. {Gamma}BMM uses multiple data sources, naturally selects the number of states and can be extended to other parametric distributions according to the number and type of data sources available. We apply it to protein and RNA levels, and promoter occupancy state of a toggle switch and show that it can be bistable, tristable, or monostable depending on its internal noise level. We show that these results are in agreement with the patterns of differentiation of model cells whose pathway choice is driven by the switch. We further apply {Gamma}BMM to a model of the MeKS module of Bacillus subtilis, and the results match experimental data, demonstrating the usability of {Gamma}BMM.

Availability: Implementation software is available upon request.

Contact: andre.sanchesribeiro@tut.fi and xiaofeng.dai@tut.fi

Associate Editor: Dr. Trey Ideker

Received on April 7, 2009; revised on May 28, 2009; accepted on June 28, 2009

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