Daniel Figueiredo,

Universidade de Aveiro


In the context of biological regulatory networks, the connection between Piecewise-linear (PWL) models and Boolean networks is well-known, since Boolean networks can be seen as simplifications of PWL models. However, due to the abstraction of BN models, some asymptotic dynamics can be lost. This is observed since some steady states of a PWL model can be forgotten by the corresponding BN, not being signaled by terminals. Reactive Boolean networks (RBN) are an intermediary kind of model which is based on the notion of switch graph, as introduced by Marcelino and Gabbay. A switch graph is a generalized graph which includes special edges which grants a notion of “memory” to a usual graph. An adapted notion of terminal is obtained for RBN and it is shown that this class of model can recover asymptotic dynamics than Boolean networks.

Finally the concept of switch graph is generalized to include weights in edges. This produces a more general class of model and its application to model biological regulatory networks is explored.


Daniel Figueiredo is a final year PhD student of Applied Mathematics at Universidade de Aveiro, supervised by Manuel Antonio Martins (Dep. Mathematics – Universidade de Aveiro) and co-supervised by Luis Soares Barbosa (Dep. Computer Science – Universidade do Minho).


Date: 2019-Nov-07     Time: 10:00:00     Room: 336

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