VCell Modeling & Analysis Software 2021-11-29T20:34:54+00:00

**Save the Date – 23rd Annual CCB Workshop**

We are pleased to announce both an online and an in-person Computational Cell Biology Workshop for 2022.

The online workshop will be hosted May 23-25, 2022, while the in-person workshop will be held July 25-27, 2022.

Additional information will be posted as we approach the registration dates for the two workshops.

Featured Speakers for Online Workshop:

Image Aurelie Carlier
Aurélie Carlier

Maastricht University

Image Padmini Rangamani
Padmini Rangamani

UC San Diego

Image Melanie Stefan
Melanie Stefan

University of Edinburgh

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 was developed with funding from the National Institute of General Medical Sciences (NIGMS) as a Biomedical Technology Research Resource at the Center for Cell Analysis and Modeling (CCAM), and is currently funded by R24 GM137787. CCAM 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?

VCell is developed at The Center for Cell Analysis & Modeling, at UConn Health. Established in 1994, CCAM consists of faculty trained in diverse backgrounds 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 acknowledge the VCell Resource in all publications. VCell is supported by NIH Grant Number R24 GM137787 from the National Institute for General Medical Sciences. And please reference the appropriate citations.

News

For additional posts see News & Events.

New model of FAK influence on YAP-TAZ

2021-09-10. VCell MathModels were used to explore how FAK activation influences YAP/TAZ translocation in a new publication by Eroume et al. in Biophysical Journal. Find links to the paper and public VCell models on our published models page. […]

New model of actin filament nucleation

2021-09-9. VCell models and COPASI parameter estimation tools were used to test molecular mechanisms for actin filament nucleation in a paper from the Loew and Pollard labs. Find links to the paper and public VCell models on our published […]

New model of Sperm Calcium

2021-7-27. A new VCell model by Korobkin et al, explores calcium oscillations in mammalian sperm. COPASI software was also utilized for parameter estimation to fit the models.   Find links to the paper and public VCell models on our […]

2021 Computational Cell Biology Workshop help June 21-23.

2021-6-24  CCAM’s annual Computational Cell Biology Workshop was again held online June 21-23, 2021.  The workshop provided instruction to over 50 individuals from around the world on mathematical modeling techniques using VCell, COPASI and SpringSaLaD software. Fifteen of the participants […]

VCell model of YAP/TAZ

2021-5-08. A new VCell model from the Rangamani lab explores how YAP/TAZ signaling integrates inputs from different biophysical properties of the cell. Find links to the paper and public VCell models on our published models page. […]

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