R. Thomas' Modeling of Biological Regulatory Networks: Introduction of Singular States in the Qualitative Dynamics

Modeling Biological Regulatory Networks with Singular States

In the field of biological regulation, models extracted from experimental works are usually complex networks comprising intertwined feedback circuits. R. Thomas and coworkers introduced a qualitative description of such regulatory networks, then they used the concept of circuit-characteristic states to identify all steady states and functional circuits. These characteristic states play an essen...

Modeling gene regulatory networks: Classical models, optimal perturbation for identification of network

Deep understanding of molecular biology has allowed emergence of new technologies like DNA decryption.  On the other hand, advancements of molecular biology have made manipulation of genetic systems simpler than ever; this promises extraordinary progress in biological, medical and biotechnological applications.  This is not an unrealistic goal since genes which are regulated by gene regulatory ...

Relating Attractors and Singular Steady States in the Logical Analysis of Bioregulatory Networks

In 1973 R. Thomas introduced a logical approach to modeling and analysis of bioregulatory networks. Given a set of Boolean functions describing the regulatory interactions, a state transition graph is constructed that captures the dynamics of the system. In the late eighties, Snoussi and Thomas extended the original framework by including singular values corresponding to interaction thresholds....

Graph-Based Modeling of Biological Regulatory Networks: Introduction of Singular States

On the conversion of multivalued gene regulatory networks to Boolean dynamics

We consider the modeling approach introduced by R. Thomas for the qualitative study of gene regulatory networks. Tools and results on regulatory networks are often concerned only with the Boolean case of this formalism. However, multivalued approaches are sometimes more suited to model biological situations. Multivalued networks can be converted to partial Boolean maps, in a way that preserves ...