This volume covers a variety of topics related to the practice of rule-based modeling, a type of mathematical modeling useful for studying biomolecular site dynamics. There is an emphasis on software tools and detailed descriptions of techniques. The chapters in this book discuss topics such as software tools and frameworks for compartmental modeling (Pycellerator, RuleBuilder, Prgy, rxncon, MSMB, and ML-Rules); tools for spatial modeling (Simmune, Smoldyn, MCell-R, SRSim, and CellOrganizer); rule-based models to analyze proteomic data; model annotation; Markov chain aggregation; BioJazz; and methods to identify model parameters (Data2Dynamics, RKappa, and BioNetFit). Written in the highly successful
Methods in Molecular Biology
series format, chapters include introductions to their respective topics, lists of the necessary resources, step-by-step, readily reproducible protocols, and tips on troubleshooting and avoiding known pitfalls.
Cutting-edge and thorough,
Modeling Biomolecular Site Dynamics: Methods and Protocols
is a valuable resource for both the novice and expert rule-based modeler. It will also appeal to systems biologists and help them enhance their studies with easy-to-read and write rule-based models.
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Illustrationen
108 farbige Abbildungen, 80 s/w Abbildungen
XIX, 423 p. 188 illus., 108 illus. in color.
ISBN-13
978-1-4939-9102-0 (9781493991020)
DOI
10.1007/978-1-4939-9102-0
Schweitzer Klassifikation
A Pycellerator Tutorial.- Using RuleBuilder to Graphically Define and Visualize BioNetGen-Language Patterns and Reaction Rules.- Strategy-Driven Exploration for Rule-Based Models of Biochemical Systems with PORGY.- Using rxncon to Develop Rule-Based Models.- Efficiently Encoding Complex Biochemical Models with the Multistate Model Builder (MSMB).- Multi-Level Modeling and Simulation of Cellular Systems: An Introduction to ML-Rules.- Using Python for Spatially Resolved Modeling with Simmune.- Rule-Based Modeling using Wildcards in the Smoldyn Simulator.- MCell-R: A Particle-Resolution Network-Free Spatial Modeling Framework.- Spatial Rule-Based Simulations: the SRSim Software.- CellOrganizer: Learning and Using Cell Geometries for Spatial Cell Simulations.- Using Mechanistic Models for Analysis of Proteomic Data.- Annotations for Rule-Based Models.- Markov Chain Aggregation and Its Application to Rule-Based Modelling.- In Silico Evolution of Signaling Networks Using Rule-Based Models: Bistable Response Dynamics.- Recipes for Analysis of Molecular Networks Using the Data2Dynamics Modeling Environment.- RKappa: Software for Analyzing Rule-Based Models.- A Step-by-Step Guide to Using BioNetFit.
