Instytut Podstawowych Problemów Techniki
Polskiej Akademii Nauk

Partnerzy

Jason Haugh

University of Warwick (GB)

Ostatnie publikacje
1.  Chylek L.A., Hu B., Blinov M.L., Emonet T., Faeder J.R., Goldstein B., Gutenkunst R.N., Haugh J.M., Lipniacki T., Posner R.G., Yang J., Hlavacek W.S., Guidelines for visualizing and annotating rule-based models, MOLECULAR BIOSYSTEMS, ISSN: 1742-206X, DOI: 10.1039/c1mb05077j, Vol.7, pp.2779-2795, 2011

Streszczenie:
Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme–substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FceRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models.

Afiliacje autorów:
Chylek L.A. - Los Alamos National Laboratory (US)
Hu B. - Los Alamos National Laboratory (US)
Blinov M.L. - University of Connecticut Health Center (US)
Emonet T. - Yale University (US)
Faeder J.R. - University of Pittsburgh School of Medicine (US)
Goldstein B. - Los Alamos National Laboratory (US)
Gutenkunst R.N. - University of Arizona (US)
Haugh J.M. - University of Warwick (GB)
Lipniacki T. - IPPT PAN
Posner R.G. - Translational Genomics Research Institute (US)
Yang J. - Clemson University (US)
Hlavacek W.S. - Los Alamos National Laboratory (US)
30p.

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