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Using rxncon to Develop Rule-Based Models
- Source :
- Modeling Biomolecular Site Dynamics ISBN: 9781493991006
- Publication Year :
- 2019
- Publisher :
- Springer New York, 2019.
-
Abstract
- We present a protocol for building, validating, and simulating models of signal transduction networks. These networks are challenging modeling targets due to the combinatorial complexity and sparse data, which have made it a major challenge even to formalize the current knowledge. To address this, the community has developed methods to model biomolecular reaction networks based on site dynamics. The strength of this approach is that reactions and states can be defined at variable resolution, which makes it possible to adapt the model resolution to the empirical data. This improves both scalability and accuracy, making it possible to formalize large models of signal transduction networks. Here, we present a method to build and validate large models of signal transduction networks. The workflow is based on rxncon, the reaction-contingency language. In a five-step process, we create a mechanistic network model, convert it into an executable Boolean model, use the Boolean model to evaluate and improve the network, and finally export the rxncon model into a rule-based format. We provide an introduction to the rxncon language and an annotated, step-by-step protocol for the workflow. Finally, we create a small model of the insulin signaling pathway to illustrate the protocol, together with some of the challenges-and some of their solutions-in modeling signal transduction.
- Subjects :
- 0303 health sciences
Rule-based modeling
Boolean model
Computer science
0206 medical engineering
Rule-based system
02 engineering and technology
computer.file_format
computer.software_genre
03 medical and health sciences
Workflow
Scalability
Data mining
Executable
Signal transduction
computer
Protocol (object-oriented programming)
020602 bioinformatics
030304 developmental biology
Network model
Subjects
Details
- ISBN :
- 978-1-4939-9100-6
- ISBNs :
- 9781493991006
- Database :
- OpenAIRE
- Journal :
- Modeling Biomolecular Site Dynamics ISBN: 9781493991006
- Accession number :
- edsair.doi...........1d4918fa70ce2ac37059f8b2008e668a