Interactive, distributed, and embedded systems often behave stochastically, for example,
when inputs, message delays, or failures conform to a probability distribution. However …

The approximation based programming paradigm is especially attractive for develo**
error-resilient applications, targeting low power embedded devices. It allows for program …

Cellular signaling is essential in information processing and decision-making. Therefore, a
variety of experimental approaches have been developed to study signaling on bulk and …

Statistical model checking (SMC) is a technique for analysis of probabilistic systems that
may be (partially) unknown. We present an SMC algorithm for (unbounded) reachability …

Approximate computing has emerged as a new paradigm to reduce the resources (eg,
design area and power) required to realize digital systems at the expense of a negligible or …

For many biological systems, a variety of simulation models exist. A new simulation model is
rarely developed from scratch, but rather revises and extends an existing one. A key …

Develo** pharmacological strategies for controlling ionizing radiation (IR)-induced cell
death is important for both mitigating radiation damage and alleviating the side effects of anti …

Monitoring disease response after intensive chemotherapy for acute myeloid leukemia
(AML) currently requires invasive bone marrow biopsies, imposing a significant burden on …

In this paper, we survey recent work on the use of statistical model checking techniques for
biological applications. We begin with an overview of the basic modelling techniques for …

Rule-based modeling with BioNetGen has been widely used to study the dynamics of
complex biochemical systems. Rule-based models can be analyzed by carrying out …