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.
Dimitrova, E. S., & Zardecki, A. (2008). Forecasting polynomial dynamics. Applied Mathematics and Computation, 204(1), 233–239. https://doi.org/10.1016/j.amc.2008.06.040