We introduce a framework for analyzing ordinary differential equation (ODE) models of
biological networks using statistical model checking (SMC). A key aspect of our work is the …

We present a statistical model checking (SMC) based framework for studying ordinary
differential equation (ODE) models of bio-pathways. We address cell-to-cell variability …

Motivation: Biopathways are often modeled as systems of ordinary differential equations
(ODEs). Such systems will usually have many unknown parameters and hence will be …

We propose an automated method for exploring kinetic parameters of stochastic
biochemical systems. The main question addressed is how the validity of an a priori given …

Automated verification of stochastic models has been proved to be an effective technique for
the analysis of a large class of stochastically behaving systems. In this paper we show how …

Formal methods hold great promise in promoting further discovery and innovation for
complicated biological systems. Models can be tested and adapted inexpensively in-silico to …

Recently, there has been considerable interest in the use of Model Checking for Systems
Biology. Unfortunately, the state space of stochastic biological models is often too large for …

The stochastic dynamics of biochemical reaction networks can be modeled using a number
of succinct formalisms all of whose semantics are expressed as Continuous Time Markov …

This report proposes a novel framework for a rigorous robustness analysis of stochastic
biochemical systems. The technique is based on probabilistic model checking. We adapt the …

Chemical Reaction Networks (CRN) constitute a formalism used to model biological
processes. When the population number is not significant and the system is well-stirred, a …