7 citations · 8 across the 3 of their papers we have counts for
5 papers
Taming Asynchrony for Attractor Detection in Large Boolean Networks (Technical Report)
Andrzej Mizera, Jun Pang, Hongyang Qu +1
Boolean networks is a well-established formalism for modelling biological systems. A vital challenge for analysing a Boolean network is to identify all the attractors. This becomes…
Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study
Jingyi Wang, Jun Sun, Qixia Yuan +1
Many automated system analysis techniques (e.g., model checking, model-based testing) rely on first obtaining a model of the system under analysis. System modeling is often done ma…
Fast Simulation of Probabilistic Boolean Networks (Technical Report)
Andrzej Mizera, Jun Pang, Qixia Yuan
Probabilistic Boolean networks (PBNs) is an important mathematical framework widely used for modelling and analysing biological systems. PBNs are suited for modelling large biologi…
Parallel Approximate Steady-state Analysis of Large Probabilistic Boolean Networks (Technical Report)
Andrzej Mizera, Jun Pang, Qixia Yuan
Probabilistic Boolean networks (PBNs) is a widely used computational framework for modelling biological systems. The steady-state dynamics of PBNs is of special interest in the ana…
Reviving the Two-state Markov Chain Approach (Technical Report)
Andrzej Mizera, Jun Pang, Qixia Yuan
Probabilistic Boolean networks (PBNs) is a well-established computational framework for modelling biological systems. The steady-state dynamics of PBNs is of crucial importance in…