CCAM Software is produced by the faculty and staff of CCAM. Our flagship application, the Virtual Cell, serves as a National Resource for Cell Analysis and Modeling. The software below ranges from applications for analyzing FRAP and other image data, (Virtual FRAP Tool, Microfilament Detector, 5-D Visualization MicroApp) to tools for generating models (BioNetGen, SyBiL).
The Virtual Cell has been specifically designed to be a web-based research tool for a wide range of scientists, from experimental cell biologists to theoretical biophysicists. Likewise the creation of models can range from the simple, to evaluate hypotheses or to interpret experimental data, to complex multi-layered models used to probe the predicted behavior of complex, highly non-linear systems. Users can build complex models with a web-based Java interface to specify compartmental topology and geometry, molecular characteristics, and relevant interaction parameters. The Virtual Cell automatically converts the biological description into a corresponding mathematical system of ordinary and/or partial differential equations.
|Users Guide and Tutorial|
|SpringSaLaD mac||SpringSaLaD linux||SpringSaLaD win|
SpringSaLaD is a particle-based, stochastic, biochemical simulation platform most suitable for modeling mesoscopic systems, which are far too large to be modeled with molecular dynamics but which require more detail than obtainable with macroscopic continuum models. In SpringSaLaD, molecules are modeled as a collection of impenetrable spheres (called “sites”) linked by stiff springs. The sites are intended to represent mesoscopic protein domains, such as an SH2 domain or a catalytic domain, and each site can be associated with a number of biochemical states, such as “active” or “inactive” for a catalytic domain. SpringSaLaD supports the full array of typical biochemical reactions: zeroeth-order reactions which model particle creation, a variety of first-order reactions such as particle decay, dissociation, and state transitions, and second-order reactions between sites for bonding reactions.
A good example a system which is best modeled with SpringSaLaD is ligand-mediated receptor clustering, where coarse-grained particle-level interactions are required but atom-level information is not of interest. In general, SpringSaLaD is best used to model mesoscopic particles (diameters of 1 – 10 nm, which could represent a functional protein domain), moderately sized systems (10 – 10,000 particles), and times scales on the order of 1 second, but no actual restriction is set on size or scale of the simulated system.
SpringSaLaD is available as JAR files for PC, Mac, and Linux. It includes a user-friendly GUI which supports all aspects of model creation, running simulations, and data analysis. The downloadable zip file also include a user’s guide and tutorial which walks the reader through a full example from model creation to data analysis.
Virtual FRAP Tool
BaSDI (Bayesian super-resolution drift inference)
Single-molecule localization based super-resolution microscopy requires accurate sample drift correction in order to achieve good results. BaSDI implements a Bayesian statistical algorithm that estimate amount of the sample drift for every image frame from the raw dataset. The inference requires no fiducial marker but requires the assumption that the drift is mostly smooth over time. A detailed description of the statistical framework for this algorithm is published, Elmokadem A, Yu J, Optimal Drift Correction for Super-resolution Localization Microscopy with Bayesian Inference, Biophys J, 2015 Nov 3;109(9):1772-80. doi: 10.1016/j.bpj.2015.09.017. PubMed Link
Octane (Super-resolution imaging and single molecule tracking software.)
The Octane is a program we developed to facilitate works involved in super-resolution optical imaging (PALM, STORM, etc.). By providing an intuitive graphical user interface front end, we hope it can serve as a useful tool for a wide range of scientists, including experimental biologists as well as physicists. The program runs as a plugin of the (extremely versatile) ImageJ software, thus can be used on any image format that is supported by ImageJ.
An ImageJ plugin designed to automate processing of sets of images of biological structures. The current implementation is for filament detection, but the plugin is built in a modular fashion so that only the engine parameters need to be changed to detect other types of structures.