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New tools for model construction, calibration and analysis

We are developing and applying new approaches to the construction, calibration and analysis of kinetic and logic-based models of complex biological processes. A major thrust is to develop a variety of methods to calibrate ODE models against experimental data in order to estimate parameter values and their uncertainty with the greatest accuracy possible. We are adapting methods from optimization theory and statistical mechanics to calibrate kinetic models, and using sampling to explore fitness landscapes and estimate parameter constraint. We are also learning to draw correct hypotheses from partially calibrated models.

Other goals are as follows:

  • Use rules-based models (BioNetGen and Kappa) and the programming language little b for meta-language programming of kinetic models
  • Develop methods to construct cell-specific pathway models based on Boolean logic
  • Modify Boolean models with fuzzy logic and logic-based ODEs to model intermediate states
  • Explore various model analysis tools (e.g., agent-based methods, model reduction methods) to extract insight from calibrated kinetic and logic-based models
  • Implement SB-Wiki, a system for model annotation, documentation and sharing based on semantic web concepts(22) and Wiki technology.
  • Develop a tool, DataRail, to manage, visualize, and process experimental data, to efficiently couple data and models
  • Develop a new framework, SB-Pipeline, to embed the tools described above and allow an effective workflow for constructing and testing models, particularly those that incorporate significant prior knowledge.

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This page last modified on September 11th, 2009