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  Evaluating the effect of perturbations in reconstructing network topologies

Markowetz, F., & Spang, R. (2003). Evaluating the effect of perturbations in reconstructing network topologies.

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 Creators:
Markowetz, Florian1, Author
Spang, Rainer2, Author           
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1Max Planck Society, ou_persistent13              
2Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              

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 Abstract: Many different Bayesian network models have been suggested to reconstruct gene expression networks from microarray data. However, little attention has been payed to the effects of small sample size and the stability of the solution. We engage in a systematic investigation of these issues. As a starting point for further research we introduce the kappa-network. It is a small Bayesian network model (5 nodes with three states) in which a parameter kappa controls the conditional probability distributions of the nodes. With data sampled from this model, we evaluate the effects of different sample sizes and of data being derived from active perturbations on the reconstruction of the origninal network topology.

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Language(s): eng - English
 Dates: 2003
 Publication Status: Issued
 Pages: online proceedings
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 Rev. Type: -
 Identifiers: eDoc: 175872
 Degree: -

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Title: 3rd International Workshop on Distributed Statistical Computing (DSC 2003)
Place of Event: Technische Universität Wien, Vienna, Austria
Start-/End Date: 2003-03-20 - 2003-03-22

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