This paper presents an evolutionary method for identifying the gene regulatory network from the observed time series data of gene expression using a system of ordinary differential...
The complexity of gene regulatory network models stems from the fact that the models should be able to represent continuous, discrete as well as stochastic aspects of gene regulati...
This paper discusses the simulation results of a model of biological development for neural networks based on a regulatory genome. The model’s results are analyzed using the fra...
Background: The incorporation of prior biological knowledge in the analysis of microarray data has become important in the reconstruction of transcription regulatory networks in a...
Peter Larsen, Eyad Almasri, Guanrao Chen, Yang Dai
Abstract. We present a systematic translation from timed models of genetic regulatory networks into products of timed automata to which one can apply verification tools in order l...