{"id":691,"date":"2016-04-26T13:56:34","date_gmt":"2016-04-26T17:56:34","guid":{"rendered":"http:\/\/ccamwp.uh.uconn.edu\/?page_id=691"},"modified":"2025-11-24T14:33:42","modified_gmt":"2025-11-24T19:33:42","slug":"ccam-software","status":"publish","type":"page","link":"https:\/\/health.uconn.edu\/cell-analysis-modeling\/ccam-software\/","title":{"rendered":"Software"},"content":{"rendered":"
\"CCAM<\/div><\/div>
\"Three<\/div><\/div>
\"Artistic<\/div><\/div><\/div>
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Virtual Cell<\/p>\n<\/div>\n

\nThe Virtual Cell<\/a> 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.<\/div>\n<\/div>\n<\/div><\/div>
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COPASI<\/p>\n<\/div>\n

COPASI<\/a> is a stand-alone software application for simulation and analysis of biochemical networks and their dynamics. COPASI supports models in the SBML standard and can simulate them using ODEs, SDEs, or Gillespie's stochastic simulation algorithm. COPASI provides a set analysis methods and parameter estimation.<\/span><\/div>\n<\/div>\n<\/div><\/div>
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SpringSaLaD<\/p>\n<\/div>\n

SpringSaLaD<\/a>\u00a0is 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.<\/div>\n<\/div>\n<\/div><\/div>
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Vivarium Collective<\/p>\n<\/div>\n

The Vivarium Collective<\/a> is a registry for open-source Vivarium-compatible simulation modules. These can be wired together to generate novel multi-scale simulations, with the most appropriate algorithm for each biological mechanism.<\/div>\n<\/div>\n<\/div><\/div>
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FIJI\/ImageJ VCell Simulation Results Viewer Plugin<\/p>\n<\/div>\n

The VCell FIJI\/ImageJ Plugin<\/a> enables the remote viewing and analysis of the VCell simulation results data sets in ImageJ, without the need to download data to your computer and import it to Fiji\/ImageJ. It supports ImageJ compatible remote storage image format *.N5. New VCell features include, spatial simulation results in VCell can be prepared for export in N5 formats but still stored on the remote server, the link to simulation results enabled them to be opened by imaging software supporting N5, and the ImageJ\/FIJI VCell Simulation Results Viewer Plugin can import VCell simulation results directly into Fiji. <\/div>\n<\/div>\n<\/div><\/div>
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Virtual FRAP Tool<\/p>\n<\/div>\n

\nAccessed through the VCell modeling and simulation environment (vcell.org<\/a>), the Virtual FRAP tool is designed to analyze FRAP, Fluorescence Recovery after Photobleaching, experiments. It is available as a tool within the VCell software, and can be used to analyze experiments that collect all of the fluorescence associated with the cell, and where the bleach region does not vary through the Z dimension. Currently, Virtual FRAP can be used to fit D and %R for either one or two diffusing components of cytosolic (soluble) proteins, or to fit off rates for binding to immobile components. It does not analyze lateral diffusion within the plasma membrane.<\/div>\n<\/div>\n<\/div><\/div>
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Octane (Super-resolution imaging and single molecule tracking software.)<\/h3>\n<\/div>\n

Yu Lab>Software<\/a><\/p>\n

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.<\/p>\n<\/div>\n<\/div>\n<\/div><\/div>

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BaSDI (Bayesian super-resolution drift inference)<\/p>\n<\/div>\n

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Please see additional software information and download information at Yu Lab>Software<\/a><\/p>\n

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<\/a><\/p>\n<\/div>\n<\/div>\n<\/div><\/div>

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BioNetGenLanguage (BNGL) code visualizer<\/p>\n<\/div>\n

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Usage and limitations of BNGL code visualizer<\/a>:<\/p>\n