Welcome to the q-bio Summer School and Conference!

The Seventh q-bio Summer School: Cell Signaling

From Q-bio

This series of lectures, which is offered at the Santa Fe campus, will be focused on modeling cell signaling. We will begin with an overview of the inherent features of cell signaling systems, including the modularity of proteins, the importance of post-translational modifications (e.g., multisite phosphorylation), and an overview of cell signaling motifs, such as kinetic proofreading, serial engagement, and regulated recruitment (co-localization of enzymes and substrates). We will then discuss how these features complicate efforts to develop predictive mechanistic models of cell signaling systems and possible solutions, in particular the rule-based modeling approach. We will cover methods for simulating a model, visualizing and annotating a model, and fitting procedures. We will make extensive use of software tools that are compatible with the BioNetGen language (BNGL) or the closely related Kappa language (http://kappalanguage.org/). An example of such a tool is BioNetGen (http://bionetgen.org). For additional information, contact Bill Hlavacek.




  • Core lecture, Monday, July 22, William S. Hlavacek
  • Core lecture, Tuesday, July 23, Wouter-Jan Rappel
  • Core lecture, Wednesday, July 24, Ryan N. Gutenkunst
  • Course-specific lecture, Monday, July 29, Lily A. Chylek
  • Course-specific lecture and RuleBender/BioNetGen/NFsim tutorial, Tuesday, July 30, James R. Faeder
  • Course-specific lecture, Wednesday, July 31, Nathan W. Lemons
  • Course-specific lecture, Thursday, August 1, Bridget S. Wilson

Computer Labs

  • TBA


  • Inherent features of cell signaling systems
  • Combinatorial complexity
  • Limitations of traditional approaches for modeling chemical kinetics
  • The rule-based modeling approach (a link to a course that covers rule-based modeling at Pittsburgh is here)
  • BioNetGen language (BNGL)
  • Visualizing and annotating a rule-based model
  • Simulation methods
  • Software tools
  • Fitting, sensitivity analysis, sloppiness

Student projects

Individual students or teams of students will work on projects. Journal clubs and faculty-recommended team projects will be announced shortly.


Recommended reading

  • TBA