Literature DB >> 22139996

Virtual Cell: computational tools for modeling in cell biology.

Diana C Resasco1, Fei Gao, Frank Morgan, Igor L Novak, James C Schaff, Boris M Slepchenko.   

Abstract

The Virtual Cell (VCell) is a general computational framework for modeling physicochemical and electrophysiological processes in living cells. Developed by the National Resource for Cell Analysis and Modeling at the University of Connecticut Health Center, it provides automated tools for simulating a wide range of cellular phenomena in space and time, both deterministically and stochastically. These computational tools allow one to couple electrophysiology and reaction kinetics with transport mechanisms, such as diffusion and directed transport, and map them onto spatial domains of various shapes, including irregular three-dimensional geometries derived from experimental images. In this article, we review new robust computational tools recently deployed in VCell for treating spatially resolved models.
Copyright © 2011 Wiley Periodicals, Inc.

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Year:  2011        PMID: 22139996      PMCID: PMC3288182          DOI: 10.1002/wsbm.165

Source DB:  PubMed          Journal:  Wiley Interdiscip Rev Syst Biol Med        ISSN: 1939-005X


  19 in total

1.  Models of eukaryotic gradient sensing: application to chemotaxis of amoebae and neutrophils.

Authors:  Andre Levchenko; Pablo A Iglesias
Journal:  Biophys J       Date:  2002-01       Impact factor: 4.033

Review 2.  The Virtual Cell: a software environment for computational cell biology.

Authors:  L M Loew; J C Schaff
Journal:  Trends Biotechnol       Date:  2001-10       Impact factor: 19.536

3.  The virtual cell: an integrated modeling environment for experimental and computational cell biology.

Authors:  Ion I Moraru; James C Schaff; Boris M Slepchenko; Leslie M Loew
Journal:  Ann N Y Acad Sci       Date:  2002-10       Impact factor: 5.691

Review 4.  Use of virtual cell in studies of cellular dynamics.

Authors:  Boris M Slepchenko; Leslie M Loew
Journal:  Int Rev Cell Mol Biol       Date:  2010       Impact factor: 6.813

5.  Stochastic simulation of chemical reactions with spatial resolution and single molecule detail.

Authors:  Steven S Andrews; Dennis Bray
Journal:  Phys Biol       Date:  2004-12       Impact factor: 2.583

6.  Tools for kinetic modeling of biochemical networks.

Authors:  Rui Alves; Fernando Antunes; Armindo Salvador
Journal:  Nat Biotechnol       Date:  2006-06       Impact factor: 54.908

7.  In vivo dynamics of Rac-membrane interactions.

Authors:  Konstadinos Moissoglu; Boris M Slepchenko; Nahum Meller; Alan F Horwitz; Martin A Schwartz
Journal:  Mol Biol Cell       Date:  2006-04-05       Impact factor: 4.138

8.  Diffusion on a Curved Surface Coupled to Diffusion in the Volume: Application to Cell Biology.

Authors:  Igor L Novak; Fei Gao; Yung-Sze Choi; Diana Resasco; James C Schaff; Boris M Slepchenko
Journal:  J Comput Phys       Date:  2007-10-01       Impact factor: 3.553

9.  A general computational framework for modeling cellular structure and function.

Authors:  J Schaff; C C Fink; B Slepchenko; J H Carson; L M Loew
Journal:  Biophys J       Date:  1997-09       Impact factor: 4.033

10.  Detailed simulations of cell biology with Smoldyn 2.1.

Authors:  Steven S Andrews; Nathan J Addy; Roger Brent; Adam P Arkin
Journal:  PLoS Comput Biol       Date:  2010-03-12       Impact factor: 4.475

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  27 in total

1.  A conservative algorithm for parabolic problems in domains with moving boundaries.

Authors:  Igor L Novak; Boris M Slepchenko
Journal:  J Comput Phys       Date:  2014-08-01       Impact factor: 3.553

2.  Modeling heterogeneous tumor growth dynamics and cell-cell interactions at single-cell and cell-population resolution.

Authors:  Leonard A Harris; Samantha Beik; Patricia M M Ozawa; Lizandra Jimenez; Alissa M Weaver
Journal:  Curr Opin Syst Biol       Date:  2019-09-16

3.  Compartmental and Spatial Rule-Based Modeling with Virtual Cell.

Authors:  Michael L Blinov; James C Schaff; Dan Vasilescu; Ion I Moraru; Judy E Bloom; Leslie M Loew
Journal:  Biophys J       Date:  2017-10-03       Impact factor: 4.033

Review 4.  Quantitative computational models of molecular self-assembly in systems biology.

Authors:  Marcus Thomas; Russell Schwartz
Journal:  Phys Biol       Date:  2017-05-23       Impact factor: 2.583

5.  Spatial modeling of cell signaling networks.

Authors:  Ann E Cowan; Ion I Moraru; James C Schaff; Boris M Slepchenko; Leslie M Loew
Journal:  Methods Cell Biol       Date:  2012       Impact factor: 1.441

Review 6.  Emerging proteomic technologies for elucidating context-dependent cellular signaling events: A big challenge of tiny proportions.

Authors:  Sarah J Parker; Koen Raedschelders; Jennifer E Van Eyk
Journal:  Proteomics       Date:  2015-02-10       Impact factor: 3.984

7.  Mad dephosphorylation at the nuclear pore is essential for asymmetric stem cell division.

Authors:  Justin Sardi; Muhammed Burak Bener; Taylor Simao; Abigail E Descoteaux; Boris M Slepchenko; Mayu Inaba
Journal:  Proc Natl Acad Sci U S A       Date:  2021-03-30       Impact factor: 11.205

8.  Rules of Engagement: A Guide to Developing Agent-Based Models.

Authors:  Marc Griesemer; Suzanne S Sindi
Journal:  Methods Mol Biol       Date:  2022

Review 9.  Machine Learning and Hybrid Methods for Metabolic Pathway Modeling.

Authors:  Miroslava Cuperlovic-Culf; Thao Nguyen-Tran; Steffany A L Bennett
Journal:  Methods Mol Biol       Date:  2023

10.  Design and evaluation of engineered protein biosensors for live-cell imaging of EGFR phosphorylation.

Authors:  Karthik Tiruthani; Adam Mischler; Shoeb Ahmed; Jessica Mahinthakumar; Jason M Haugh; Balaji M Rao
Journal:  Sci Signal       Date:  2019-06-04       Impact factor: 8.192

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