Abstract. This paper introduces a model for simulating regulatory networks that is capable of reproducing spatial and temporal expression patterns in developmental processes. The m...
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Starting from the logical description of gene regulatory networks developed by R. Thomas, we introduce an enhanced modelling approach based on timed automata. We obtain a refined ...
Formal verification based on model checking provides a powerful technology to query qualitative models of dynamical systems. The application of model-checking approaches is hamper...
Pedro T. Monteiro, Delphine Ropers, Radu Mateescu,...
In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...