Molecular self-assembly is the dominant form of chemical reaction in living systems, yet
efforts at systems biology modeling are only beginning to appreciate the need for and …

Background The combined effects of biological variability and measurement-related errors
on cancer sequencing data remain largely unexplored. However, the spatio-temporal …

Lattice-based stochastic simulators are commonly used to study biological reaction-diffusion
processes. Some of these schemes that are based on the reaction-diffusion master equation …

Domain-specific modeling languages (DSMLs) facilitate concise and succinct model
descriptions. DSMLs are commonly realized by defining a custom grammar and executing …

Particle-based simulation is a powerful approach for modeling systems and processes of
entities interacting in continuous space. One way to validate a particle-based simulation is to …

Background To study cell biological phenomena which depend on diffusion, active transport
processes, or the locations of species, modeling and simulation studies need to take space …

Biological cells are the prototypical example of active matter. Cells sense and respond to
mechanical, chemical and electrical environmental stimuli with a range of behaviors …

Rule-based modeling is an established paradigm for specifying simulation models of
biochemical reaction networks. The expressiveness of rule-based modeling languages …

Retinopathy is one of the leading causes of visual impairment in the developed world, it is
provoked by complications of mellitus. The consequence of retina complications are exudate …

ML-Rules is a rule-based language for multi-level modeling and simulation. ML-Rules
supports dynamic nesting of entities and applying arbitrary functions on entity attributes and …