Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.
Subscribe

Sci. STKE, 18 July 2006
Vol. 2006, Issue 344, p. re6
[DOI: 10.1126/stke.3442006re6]

Rules for Modeling Signal-Transduction Systems

William S. Hlavacek1*, James R. Faeder2, Michael L. Blinov3, Richard G. Posner4, Michael Hucka5, and Walter Fontana6

1Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
2Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
3Center for Cell Analysis and Modeling, University of Connecticut Health Center, Farmington, CT 06030, USA.
4Translational Genomics Research Institute, Phoenix, AZ 85004, USA.
5Control and Dynamical Systems, California Institute of Technology, Pasadena, CA 91125, USA.
6Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.

Gloss: Signaling molecules that control cellular regulation operate in complex networks of molecular interactions within the cell. Many of the individual proteins undergo multiple posttranslational modifications and can thus exist in numerous biochemically distinct states. We explore how mathematical models can cope with such complexity when intuition is insufficient to understand a regulatory scheme. We review approaches to creation of mathematical models of signaling systems with strategies that keep the models from being unwieldy but still allow them to accurately reflect biological systems. We discuss the translation of information about such signaling pathways into a computer-readable language that could allow interoperability of various models. The review has 10 figures and 155 citations and contains Web links to Web sites relevant to the various modeling efforts discussed.

*Corresponding author. E-mail, wish{at}lanl.gov

Citation: W. S. Hlavacek, J. R. Faeder, M. L. Blinov, R. G. Posner, M. Hucka, W. Fontana, Rules for Modeling Signal-Transduction Systems. Sci. STKE 2006, re6 (2006).

THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
Decoding the Language of Phosphorylation Site Dynamics.
L. A. Chylek (2013)
Science Signaling 6, jc2
   Abstract »    Full Text »    PDF »
The Simmune Modeler visual interface for creating signaling networks based on bi-molecular interactions.
F. Zhang, B. R. Angermann, and M. Meier-Schellersheim (2013)
Bioinformatics 29, 1229-1230
   Abstract »    Full Text »    PDF »
A Computational Model for Early Events in B Cell Antigen Receptor Signaling: Analysis of the Roles of Lyn and Fyn.
D. Barua, W. S. Hlavacek, and T. Lipniacki (2012)
J. Immunol. 189, 646-658
   Abstract »    Full Text »    PDF »
Computational Approaches for Analyzing Information Flow in Biological Networks.
B. Kholodenko, M. B. Yaffe, and W. Kolch (2012)
Science Signaling 5, re1
   Abstract »    Full Text »    PDF »
The Evolution of the Phage Shock Protein Response System: Interplay between Protein Function, Genomic Organization, and System Function.
M. Huvet, T. Toni, X. Sheng, T. Thorne, G. Jovanovic, C. Engl, M. Buck, J. W. Pinney, and M. P. H. Stumpf (2011)
Mol. Biol. Evol. 28, 1141-1155
   Abstract »    Full Text »    PDF »
CplexA: a Mathematica package to study macromolecular-assembly control of gene expression.
J. M. G. Vilar and L. Saiz (2010)
Bioinformatics 26, 2060-2061
   Abstract »    Full Text »    PDF »
Decoupling of Receptor and Downstream Signals in the Akt Pathway by Its Low-Pass Filter Characteristics.
K. A. Fujita, Y. Toyoshima, S. Uda, Y.-i. Ozaki, H. Kubota, and S. Kuroda (2010)
Science Signaling 3, ra56
   Abstract »    Full Text »    PDF »
Perspectives for Computer Modeling in the Study of T Cell Activation.
J. Coward, R. N. Germain, and G. Altan-Bonnet (2010)
Cold Spring Harb Perspect Biol 2, a005538
   Abstract »    Full Text »    PDF »
Hematopoiesis and its disorders: a systems biology approach.
Z. L. Whichard, C. A. Sarkar, M. Kimmel, and S. J. Corey (2010)
Blood 115, 2339-2347
   Abstract »    Full Text »    PDF »
The Complexity of Cell Signaling and the Need for a New Mechanics.
W. S. Hlavacek and J. R. Faeder (2009)
Science Signaling 2, pe46
   Abstract »    Full Text »    PDF »
Computational systems biology of the cell cycle.
A. Csikasz-Nagy (2009)
Brief Bioinform 10, 424-434
   Abstract »    Full Text »    PDF »
Science Signaling Podcast: 30 June 2009.
U. B. Nielsen and A. M. VanHook (2009)
Science Signaling 2, pc12
   Abstract »    Full Text »
GetBonNie for building, analyzing and sharing rule-based models.
B. Hu, G. Matthew Fricke, J. R. Faeder, R. G. Posner, and W. S. Hlavacek (2009)
Bioinformatics 25, 1457-1460
   Abstract »    Full Text »    PDF »
Simulation of large-scale rule-based models.
J. Colvin, M. I. Monine, J. R. Faeder, W. S. Hlavacek, D. D. Von Hoff, and R. G. Posner (2009)
Bioinformatics 25, 910-917
   Abstract »    Full Text »    PDF »
Kinetic Proofreading of Ligand-Fc{epsilon}RI Interactions May Persist beyond LAT Phosphorylation.
C. Torigoe, J. R. Faeder, J. M. Oliver, and B. Goldstein (2007)
J. Immunol. 178, 3530-3535
   Abstract »    Full Text »    PDF »

To Advertise     Find Products

Science Signaling. ISSN 1937-9145 (online), 1945-0877 (print). Pre-2008: Science's STKE. ISSN 1525-8882