Review of Systems Biology Simulation Tools for Translational Research

Systems biology models and simulation tools are critical components for bridging molecular biology with predictive medicine. We report a systematic comparison of popular simulation tools, including CellDesigner, COPASI and VirtualCell, to facilitate translational research in genomics, proteomics and systems biology. Different tools evaluating the same model may produce dissimilar results. This inconsistency is a roadblock to developing patient-customized disease progression models which reduce uncertainty in clinical decisions. We implement existing molecular-level SBML and CellML and compare simulation results with published data. Preliminary results suggest some tools perform better in terms of numerical stability to determine true model behavior. Furthermore, we uncover several worrying issues: (1) disparities between tools in terms of solver algorithms and language format, (2) lack of interactivity between users and tools, (3) lack of standardization for systems biology modeling languages and (4) need for models addressing specific pressing clinical objectives such as cancer disease progression.