The reverse engineering method of gene regulatory networks, recently implemented by Laubenbacher and Stigler, is used to generate a multivariate time series with a finite set of levels. A formalism of fuzzy control allows one to forecast the evolutionary behavior of a network. When the multivariate time series is converted to a single-component series, an excellent agreement is obtained between the actual and forecasted values. The tests include both simulated and realistic models. For a binary model, with random bit changes simulating mutations, this approach can be used to detect anomalies in the network evolution. © 2008 Elsevier Inc. All rights reserved.
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