One-stop simulation shopping: deterministic (compartmental ODE or reaction-diffusion-advection PDE), stochastic reactions (several SSA solvers), spatial stochastic (reaction-diffusion with Smoldyn), hybrid deterministic/stochastic and network-free agent based simulations. Support for membrane flux, lateral membrane diffusion and electrophysiology. Models can be formulated as an explicit network or generated from graphically expressed rules.
VCell is free and has automatic installers for Windows, Mac OS and Linux.
Inexperienced modelers enter reactions and pathways in a biology-based interface; VCell automatically creates the math for you. Experienced modelers can enter math directly.
Simulations can run on our remote servers from any low-cost laptop; optionally simulations can also be run locally without an internet connection.
Model geometries may be derived from idealized analytical expressions or from experimental 2D or 3D microscope images.
Models and simulations can be accessed from anywhere; models can be shared among collaborators or made publicly available.
SpringSaLaD is a stand-alone software tool to explicitly model binding events and state changes among multivalent molecules. It is one of the first algorithms to account for crowding effects within multimolecular clusters. Spring SaLaD models proteins as sets of reactive sites (spheres) connected by stiff springs. The impenetrable spheres capture excluded volume and steric hindrance effects. Langevin dynamics are used to model diffusion of each reaction site, and binding reactions are governed by probability based on diffusion coefficients of the sites, the site radii and the macroscopic on rate. Go here to download the software or read more about the about Spring SaLaD.
Please reference the Virtual Cell Resource in your publications; grant # P41 GM103313.
2017-07-10. A new publication in Biophysical Journal by Song et al. uses a VCell model to define mechanisms for signal amplification in the PLC/PKC pathway during chemotaxis. Link to the publication and view model details from […]
7-1-2017. CCAM welcomes several undergraduates and a graduate rotation student who are working on projects related to VCell this summer . Undergraduate students include Keeyan Ghoreshi, Anvin Thomas, Natalie de la Garrique and Shahan Kamal […]
VCell was pleased and honored to host its 18th annual VCell Short Course on June 12-14, 2017. Twelve national and international scientists traveled to work with VCell developers and administrators to construct Virtual Cell models based […]
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 perform simulations, and analysis of simulation results, offering the choice of multiple physical approximations and simulation technologies to appropriately model a particular system. The BioModel interface provides an intuitive interface to construct models using either pathway diagrams or rules and from a single model of the physiology allows a choice of compartmental (0 dimensions) or spatial (1,2 or3 dimensions) applications of the physiology that can apply stochastic, determistic, or hybrid stochastic/deterministic solvers. Applications are automatically translated into full mathematical descriptions of reaction and diffusion systems and then solved via fully validated numerical methods. A MathModel interface provides a direct interface to develop models using a math description language. VCell supports multiple biophysical mechanisms, including reaction kinetics, diffusion, flow, membrane transport, lateral membrane diffusion and electrophysiology.
Symmetry and scale orient min protein patterns in shaped bacterial sculptures.
VCell spatial model of oscillating Min proteins in bacteria sculpted into defined shapes based on experimental observations demonstrated that oscillation patterns directly capture the symmetry and scale of the cell boundary.
Wu, F., B.G. van Schie, J.E. Keymer, and C. Dekker. Nat Nanotechnol 2015. 10:719-726. PMID 26098227.
Pancreatic beta cell g-protein coupled receptors and second messenger interactions: A systems biology computational analysis.
VCell analysis coupling glucose metabolism, membrane potential, G-protein coupled receptors and cytosolic second messengers including calcium, cAMP and PLC. The work demonstrates that studies of mutliple agonists and interacting pathways can help to predict pharmacological targets for modulating insulin secretion in beta cells.
Fridlyand, L.E., and L.H. Philipson. PLoS One 2016. 11:e0152869. PMID 27138453.
Synaptic activity regulates the abundance and binding of complexin.
The flux of specific protein constituents into and out of synaptic boutons in a living organism, Caenorhabditis elegans, explored using a combination of fluorescence photoactivation imaging experiments coupled with VCell spatial modeling.
Wragg, R.T., G. Gouzer, J. Bai, G. Arianna, T.A. Ryan, and J.S. Dittman. Biophys J 2015. 108:1318-1329. PMID 25809246.
From START to FINISH: Computational analysis of cell cycle control in budding yeast.
A new comprehensive mathematical model of cell cycle progression in yeast is reproduced in VCell. The model accounts for phenotypes of 257 mutant yeast strains and predicted 30 phenotypes of novel allele combinations.
Kraikivski, P., K.C. Chen, T. Laomettachit, T.M. Murali, and J.J. Tyson.
Npj Systems Biology And Applications 2015. 1:15016. http://dx.doi.org/10.1038/npjsba.2015.16.
Dynamics of phosphoinositide-dependent signaling in sympathetic neurons. Kruse, M., O. Vivas, A. Traynor-Kaplan, and B. Hille.
A VCell model representing a quantitative description of phosphoinositide metabolism in neurons. Measurements coupled with modeling reveal that PIP2 synthesis is several fold faster in sympathetic neurons as compared to an electrically nonexcitable cell line.
Kruse, M., O. Vivas, A. Traynor-Kaplan, and B. Hille.
J Neurosci 2016. 36:1386-1400. PMID 26818524.
Hysteresis-like binding of coagulation factors x/xa to procoagulant activated platelets and phospholipids results from multistep association and membrane-dependent multimerization.
VCell models provide insight into how multi-step binding and dissociation “lock” coagulation factors on the membrane in the face of signficant flow.
Podoplelova, N.A., A.N. Sveshnikova, J.H. Kurasawa, A.G. Sarafanov, H. Chambost, S.A. Vasil'ev, I.A. Demina, F.I. Ataullakhanov, M.C. Alessi, and M.A. Panteleev. 2016. Biochim Biophys Acta 1858:1216-1227. PMID 26874201.
Who Are We?
The Virtual Cell is currently developed and funded as a National Resource Center, National Resource for Cell Analysis and Modeling (NRCAM), by the National Institute of General Medical Sciences(NIGMS), grant number P41 GM103313. NRCAM continues to develop new technologies for mathematical models of cell and systems biology through development of new physical formulations of biological mechanisms, developing the numerical methods for mathematically simulating these mechanisms, and bulding software infrastructure to deliver these tools for different types of modeling applications including large reaction network applications, spatial applications and detailed molecular interactions. Meet the VCell Team.
Where Are We?
NRCAM, responsible for the development of VCell, resides at The Center for Cell Analysis & Modeling, at UConn Health. CCAM, established in 1994, consists of expertly trained faculty of varying backgrounds. This diverse wealth of knowledge ranges from chemistry, physics, and experimental cell biology to software engineering. Research at CCAM focuses on the development of new approaches for in vivo measurements and manipulation of molecular events within the cell, as well as new computational approaches to organize such data into quantitative models. CCAM is home to the Microscopy Facility, housing numerous extensive fluorescent imaging microscopes, and the High Performance Computing facility.
What Our Users Say!
“Searching through existing software packages, our attention focused on Virtual Cell….For solving differential equations, as well as storing and sharing models, Virtual Cell provides free, remote solvers and storage servers available to a worldwide community of users.”
Baik J, Rosania GR.
2013 Modeling and Simulation of Intracellular Drug Transport and Disposition Pathways with Virtual Cell.
Journal of pharmaceutics & pharmacology:1(1) .
“A key advantage of Virtual Cell is that the math is performed “behind the scenes”, so the user can focus on the biochemical reactions and biology of interest. Virtual Cell was developed … to be a simple yet powerful tool to allow students and biologists with relatively little math background to perform computational modeling.”
Greenwald EC, Polanowska-Grabowska RK, Saucerman JJ. 2014. Integrating fluorescent biosensor data using computational models. Methods in Molecular Biology:1071:227-48.
“An advantage of the compartmentalized models supported by Virtual Cell is the ease of building complex, but well constrained models that are informed by experimental data.”
Hake, J., P.M. Kekenes-Huskey, and A.D. McCulloch. 2014. Computational modeling of subcellular transport and signaling.
Current Opinion in Structural Biology. 25:92-97.
The Virtual Cell is a software modeling environment for quantitative cell biological research.
Users can create simple or complex multi-layered models with a Java web-based interface. Distinct biological and mathematical frameworks exist within a single graphical interface designed for experimental cell biologists or theoretical biophysicists.