The long-term objective of our research is to enable the development of reliable predictive models of biological systems at the cellular level. To meet this object we have a number of areas that we work on, these include:

Software (both visualization and high-performance code), Standards (for the free and unambiguous exchange of models between researchers), Theory (To allow us to understand the
rational for biological networks and link experiments with computation), and Wet Lab (To investigate the ability to re-engineer living systems).


Tellurium Python Platform (Python based one-stop platform for all things modeling in systems biology)

libRoadRunner SBML Simulation Library (This is the fastest and most easily hosted SBML simulation library available today)

pathwayDesigner (A visual design tool for drawing and simulating networks in systems biology)

TinkerCell (A visual design tool for drawing and simulating networks in synthetic biology)

SBW (A modular framework for connecting disparate software applications)


Enumerated Networks Db


SBOL – Synthetic Biology Open Language

SBOL-Visual – Synthetic Biology Open Language Visual

SED-ML – Simulation Experiment Description Markup Language

SBML – Systems Biology Markup Language


Control Theory

Control and regulation of pathways via negative feedback (2017)

Stochastic Systems

Web Lab

Evolutionary Stability of Synthetic Circuits


Jim burns Thesis Download Page

New Areas of Research that have not yet been published

Machine Learning Applications in Systems Biology

Hardware Assisted Modeling for Extreme Performance

New Approaches to Modeling Complex Systems