Online simulation and visualization

//Online simulation and visualization

Models represent our knowledge, observations and hypotheses in a testable digital framework. Because models are digital, it should be easy to reuse models and reproduce simulation results. However, many dynamic biochemical models are not reusable and many simulation results are not reproducible, including models and simulation results reported in standard formats such as the Systems Biology Markup Language (SBML) and the Simulation Experiment Description Markup Language (SED-ML). This irreproducibility limits the impact of modeling by inhibiting researchers from reusing models and simulation results for additional studies and combining models of individual biological processes into meta-models of entire biological systems.

Currently, models are hard to reuse and simulations are hard to reproduce because (a) few researchers report the metadata needed to reproduce simulations, (b) there are many incompatible simulators, (c) there is no simulation results repository, (d) there is no standard for reducing simulation results, (e) there is no standard for describing results visualizations, and (f) there are inadequate tools for visualizing simulation results.

To address these problems, we will develop novel tools and public servers for (a) using existing simulators to reproducibly simulate a wide range of models and (b) storing and (c) visualizing simulation results:

  1. We will build a database for storing models, simulation experiments, their results, and their metadata which will mint DOIs and support queries over simulation results. The system will help researchers share and retrieve simulation results and apply big data analytics to simulation results. In turn, the system will help researchers reuse simulation experiments and reproduce simulation results.
  2. We will build a simulation system which provides a common interface to multiple simulators that each support individual simulation algorithms and modeling domains. This will make it easy for researchers to reuse models and reproduce simulations without having to install domain-specific simulators.
  3. We will build a web-based system for using the simulation system and simulation results database to interactively simulate and visualize models in a browser. This will enable researchers to retrieve deposited simulation results, request new simulations, and visually analyze simulation results.

To ensure our tools advance biomodeling, we will develop our tools in conjunction with several CPs and SPs which will provide model repositories and journals web-based tools for interactively simulating and visualizing reported models. These CPs will push us to develop user-friendly tools, and we will pull the CPs to require model authors to annotate their simulation experiments so they are reproducible.

To help researchers use our software, we will work with TR&Ds 1 and 2 to combine our software into a reproducible modeling workflow. We will also extensively document our software and distribute it open-source. In addition, as part of the Training and Dissemination Core, we will develop tutorials and organize workshops.



A high performance and portable simulation engine for systems and synthetic biology. I can run on many platforms including Windows, Mac OS, and Linux. libRoadRunner is major rewrite of the original C# roadRunner developed by [...]


VCell (Virtual Cell) is a comprehensive platform for modeling cell biological systems that is built on a central database and disseminated as a web application. VCell permits construction of models, application of numerical solvers to [...]


WholeCellSimDB is a database of whole-cell model simulations designed to make it easy for researchers to explore and analyze whole-cell model predictions.


WholeCellViz is a web-based software program for visually analyzing whole-cell simulations.


  • Complexity and modularity of intracellular networks: a systematic approach for modelling and simulation
    Blinov ML, Ruebenacker O and Moraru II
    IET Syst Biol 2, 5: 363-368 (2008)
  • Guidelines for reproducibly building and simulating systems biology models
    Medley JK, Goldberg AP and Karr JR
    IEEE Trans Biomed Eng, (2016)
  • Modeling without borders: creating and annotating VCell models using the web
    Blinov ML, Ruebenacker O, Schaff JC and Moraru II
    Int Symp Bioinformatics Research Applications, 3-17 (2010)
  • Spatial modeling of cell signaling networks
    Cowan AE, Moraru II, Schaff JC, Slepchenko BM and Loew LM
    Meth Cell Biol 110, 195 (2012)
  • The Virtual Cell project
    Loew LM, Schaff JC, Slepchenko BM and Moraru II
    Systems Biomedicine, 273 (2010)
  • Virtual Cell (VCell) Modeling and Analysis Platform
    Moraru II
    Encyc Syst Biol, 2342–2347 (2013)
  • Virtual Cell modelling and simulation software environment
    Moraru II, Schaff JC, Slepchenko BM, Blinov ML, Morgan F, Lakshminarayana A, Gao F, Li Y and Loew LM
    IET Syst Biol 2, 5: 352–362 (2008)
  • WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions
    Karr JR, Phillips NC and Covert MW
    Database, pii: bau095 (2014)
  • WholeCellViz: data visualization for whole-cell models
    Lee R, Karr JR and Covert MW
    BMC Bioinformatics 14, 253 (2013)

Collaborative projects

BioModels model repository

Henning Hermjakob The European Bioinformatics Institute Cambridge, UK

JWS Online modeling environment

Jacky Snoep Stellenbosch University Stellenbosch, South Africa

Virtual Cell modeling environment

Leslie Loew Professor University of Connecticut Health Center Farmington, CT, USA

Service projects

Biophysical Journal

Les Loew Editor-In- Chief, Biophysical Journal Professor, University of Connecticut Health Center Farmington, CT, USA

Cell Systems

Craig Mak Editor, Cell Systems Cambridge, MA, USA


Maarten Cleeren Elsevier Amsterdam, NL

PRiME: Program for Research on Immune Modeling and Experimentation

Stuart Sealfon Professor Neurology, Neurobiology, and Pharmacology & Systems Therapeutics Icahn School of Medicine at Mount Sinai New York, NY, USA


Dr. Joy Ku Stanford University Stanford, CA, USA

Systems Biology Center New York

Ravi Iyengar Professor, Department of Pharmacology and Systems Therapeutics Icahn School of Medicine at Mount Sinai New York, NY, USA


Michael Blinov
Michael BlinovCo-Investigator
Assistant Professor, University of Connecticut Health Center
Ion Mororaru
Ion MororaruProject Director
Associate Professor, University of Connecticut Health Center
Dan Vasilescu
Dan Vasilescu
Software Developer, University of Connecticut Health Center