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Sci. Signal., 16 March 2010
[DOI: 10.1126/scisignal.2000517]

Supplementary Materials for:

Inferring Signaling Pathway Topologies from Multiple Perturbation Measurements of Specific Biochemical Species

Tian-Rui Xu, Vladislav Vyshemirsky, Amélie Gormand, Alex von Kriegsheim, Mark Girolami*, George S. Baillie, Dominic Ketley, Allan J. Dunlop, Graeme Milligan, Miles D. Houslay, Walter Kolch*

*To whom correspondence should be addressed. E-mail: girolami{at}dcs.gla.ac.uk (M.G.) and walter.kolch{at}ucd.ie (W.K.).

This PDF file includes:

  • Section 1. The information content in observations of varying chemical species
  • Section 2. Methods for biochemical experiments
  • Section 3. Mathematical models
  • Section 4. Bayesian statistical inference
  • Section 5. Sufficiency of data sets used in this study
  • References
  • Fig. S1. The structure of crosstalk between the cAMP and ERK pathways.
  • Fig. S2. Effect of changes in cAMP signaling on EGF-stimulated ERK activation.
  • Fig. S3. Rap1 does not interfere with Raf-1 activation and does not mediate cAMP-induced Raf-1 inhibition.
  • Fig. S4. Raf-1 and B-Raf localization.
  • Figs. S5 to S8. Detailed diagrammatic representation of models 1 through 4.
  • Fig. S9. Parameter posterior and the prior for the limiting rate of PKA deactivation in model 2.
  • Fig. S10. Parameter posterior for the rate of SOS inhibition with ERK-PP in model 2.
  • Fig. S11. Eigenvalues of the correlation matrix for the parameter posterior of model 2.
  • Fig. S12. Behaviors predicted for the EGF stimulation of PC12 cells.
  • Fig. S13 to S16. Predictions with models 1 through 4.
  • Fig. S17. Logarithms of marginal likelihoods for the models used in this study correspond to the weight of experimental evidence supporting each of the corresponding hypotheses.
  • Fig. S18. Posterior distributions for SOS activation limiting rate in model 2 inferred from a limited data set.
  • Fig. S19. Posterior distribution for Km in PKA activation by PKA agonist in model 2 inferred from a limited data set.
  • Fig. S20. Posterior distribution for Km in PKA activation by PKA agonist in model 2 inferred from the complete set of data.
  • Figs. S21 to S23. Kullback-Leibler divergence values for the parameters of models 1 to 4.
  • Table S1. Comparative informativeness of data sets with single-species observations.
  • Tables S2 to S9. Tables of experimental data for each experimental condition.

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Technical Details

Format: Adobe Acrobat PDF

Size: 2.7 MB

Other Supplementary Material for this manuscript includes the following:

Models 1 to 4 in SBML XML

[Download Models 1 to 4 (Compressed)]

Technical Details

Format: XML

Size: 10 KB (compressed); 123 KB (decompressed)

CORRECTED 4 JUNE 2012: The authors found a syntax error in the last line of the SBML models 3 and 4 and this error prevents the files from running. The compressed files above have the originally published versions with the syntax error. Updated versions of these two files are now available:

[Updated Model 3]

[Updated Model 4]


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Citation: T.-R. Xu, V. Vyshemirsky, A. Gormand, A. von Kriegsheim, M. Girolami, G. S. Baillie, D. Ketley, A. J. Dunlop, G. Milligan, M. D. Houslay, W. Kolch, Inferring Signaling Pathway Topologies from Multiple Perturbation Measurements of Specific Biochemical Species. Sci. Signal. 3, ra20 (2010).

© 2010 American Association for the Advancement of Science


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