12 citations · 20 across the 3 of their papers we have counts for
7 papers
Reducing Boolean Networks with Backward Boolean Equivalence
Georgios Argyris, Alberto Lluch Lafuente, Mirco Tribastone +2
Boolean Networks (BNs) are established models to qualitatively describe biological systems. The analysis of BNs might be infeasible for medium to large BNs due to the state-space e…
Efficient Local Computation of Differential Bisimulations via Coupling and Up-to Methods
Giorgio Bacci, Giovanni Bacci, Kim G. Larsen +3
We introduce polynomial couplings, a generalization of probabilistic couplings, to develop an algorithm for the computation of equivalence relations which can be interpreted as a l…
Exact maximal reduction of stochastic reaction networks by species lumping
Luca Cardelli, Isabel Cristina Perez-Verona, Mirco Tribastone +3
Motivation: Stochastic reaction networks are a widespread model to describe biological systems where the presence of noise is relevant, such as in cell regulatory processes. Unfort…
CLUE: Exact maximal reduction of kinetic models by constrained lumping of differential equations
Alexey Ovchinnikov, Isabel Cristina Pérez Verona, Gleb Pogudin +1
Motivation: Detailed mechanistic models of biological processes can pose significant challenges for analysis and parameter estimations due to the large number of equations used to…
Learning Queuing Networks by Recurrent Neural Networks
Giulio Garbi, Emilio Incerto, Mirco Tribastone
It is well known that building analytical performance models in practice is difficult because it requires a considerable degree of proficiency in the underlying mathematics. In thi…
Syntactic Markovian Bisimulation for Chemical Reaction Networks
Luca Cardelli, Mirco Tribastone, Max Tschaikowski +1
In chemical reaction networks (CRNs) with stochastic semantics based on continuous-time Markov chains (CTMCs), the typically large populations of species cause combinatorially larg…