VCell Modeling & Analysis Software 2018-10-19T15:29:44+00:00

VCell

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.

  • One-stop simulation shopping: deterministic (compartmental ODE or reaction-diffusion-advection PDE with support for 2D kinematics), stochastic reactions (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.
  • Explicit network or graphically expressed rules can be used to model
  • Free with automatic installers for Windows, Mac OS and Linux.
  • Biology-based interface for inexperienced modelers; enter reactions and pathways and VCell automatically creates the math for you. Experienced modelers can enter math directly.
  • Our remote servers can run complex simulations from any low-cost laptop
  • Geometries from 2D or 3D microscope images or from idealized analytical expressions.
  • Access models and simulations from anywhere using the VCell database; models can be shared among collaborators or made publicly available.

SpringSaLaD

SpringSaLaDSpringSaLaD 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.

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.

Please reference the Virtual Cell Resource
in your publications; grant # P41 GM103313.

News

For additional posts see News & Events.

19th Annual VCell Short Course

2018-6-18  VCell hosted  its 19th annual VCell Short Course on June 12-14, 2018. Ten scientists traveled to work with the VCell team to construct Virtual Cell models […]

VCell 7.0 with kinematics released

2018-3-15  Announcing the release of VCell 7.0.  VCell 7 includes new 2D kinematics functionality for solving reaction diffusion equations within moving boundaries.  To support models of […]

Leslie Loew awarded 2018 Biophysical Society Distinguished Service Award

2018-02-21.  Leslie Loew received the Distinguished Service Award of the Biophysical Society at its 2017 annual meeting February 17-21. The award acknowledged his ongoing […]

New publication on how cell shape information alters phenotype features VCell model

2017-12-15.  A new publication from the Iyngar, Hone and He laboratories using Vcell among a number of other modeling strategies to explore how cell shape […]

SpringSaLaD version 2 released

11-30-2017. Version 2 of the SpringSaLaD software was released today. The primary new feature is the ability to directly build models from atomic coordinates […]

VCell Partners

VCell acknowledges our collaborative partners that enhance VCell capabilities

Collaborations currently in development

Software Associates

EJ Technologies

VCell uses Install4J, a multi-platform installer builder to create our executables.

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.

Funding

NIHBTR
NIGMS