|
|
|
|
QBSS17 CS
This series of lectures will be focused on modeling cell signaling. We will begin with a brief overview of the hallmark features of cell signaling systems. We will then discuss how these features complicate efforts to develop predictive mechanistic models of cell signaling systems. We then introduce the rule-based modeling approach. We will cover simulation methods, sensitivity analysis, and parameter identification. We will make use of software tools that are compatible with the BioNetGen language (BNGL). An example of such a tool is BioNetGen (http://bionetgen.org). For additional information, contact Bill Hlavacek.
Contents
About the Cell Signaling focus area
Lead organizer: Bill Hlavacek (E-mail)
Faculty
- James R. Faeder, University of Pittsburgh School of Medicine
- Ryan N. Gutenkunst, University of Arizona
- William S. Hlavacek, Los Alamos National Laboratory
Topics
- Parameter estimation and sensitivity analysis
- Rule-based modeling
- Spatial modeling
Projects
- A mentored project will be organized that involves using RuleBender, BioNetGen and NFsim
Software
Please install the following software to prepare for scheduled computer labs:
- BioNetFit
- COPASI
- MATLAB (MathWorks, Natick, MA) - license available courtesy of MathWorks if required (contact organizers for details)
- MCell and CellBlender
- MCell is a spatial simulator based on Brownian dynamics and CellBlender is a Blendor-based interface to MCell.
- BioNetGen
- RuleBender is an Eclipse-based IDE for BioNetGen and NFsim, which provide deterministic and stochastic simulation capabilities appropriate in the well-mixed limit.
- These tools are freely available and easy to install on most platforms (Mac OS, Windows, Linux). They enable rule-based modeling of cellular regulatory systems.
- Download all the rule-based modeling software at http://bionetgen.org/index.php/Download
Please also familiarize yourself with BioModels Database.
Recommended Reading
- Modeling for (physical) biologists: an introduction to the rule-based approach (preprint version)
- Multi-state modeling of biomolecules (The most informative Wikipedia page about rule-based modeling)
