Modeling Biomolecular Site Dynamics: Methods and Protocols

by Hlavacek, William S.

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Title Statements

Full title :Modeling Biomolecular Site Dynamics : Methods and Protocols.

Summary

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.

Edition Statements

Publication Date:2019.

Publication Statements

Publisher(s):Springer
Place of Publication:New York, NY
Language:eng
Publication Date:2019.

Notes

Chapter 5: Efficiently Encoding Complex Biochemical Models with the Multistate Model Builder (MSMB)

The Physical Object

Description:1 online resource (435 pages)

Edition Identifiers

ISBN:9781493991020, 1493991027
DOI:10.1007/978-1-4939-9102-0.
oclc:on1122913712
LC Classification:QH301-705
Dewey Decimal:570.285

Intro; Foreword; A Novel Approach for Systems Biology Modeling; Strengths of Rule-Based Modeling; Combinatorial Complexity; Formal Representation of Biological Knowledge; Static Analysis Tools; Current Applications of Rule-Based Modeling; Summary; References; Preface; Contents; Contributors; Chapter 1: A Pycellerator Tutorial; 1 Introduction; 2 Materials; 2.1 Arrows; 2.1.1 Mass Action; 2.1.2 Enzymatic Expansion; 2.1.3 Michaelis-Menten-Henri-Briggs-Haldane Approximation; 2.1.4 Hill Functions; 2.1.5 GRN Arrows; 2.1.6 Rational Functions; 2.1.7 Generalized MWC; 2.1.8 NHCA

2.1.9 User Defined Arrows2.1.10 Cascades; 2.2 Flux Models; 2.3 Functions; 2.4 Assignments; 2.5 Initial Conditions; 2.6 Parameter Values; 2.7 Frozen Variables; 2.8 Identifiers and Symbols; 3 Methods; 3.1 Requirements; 3.1.1 Install Python; 3.1.2 Pycellerator Installation; 3.2 Model Instantiation and Simulation; 3.2.1 Plot Time Course in a Notebook; 3.2.2 Run Auto-generated Code as Stand-Alone Program; 3.2.3 Run and Plot a Model from the Command Shell; 3.2.4 Perform Parametric Tweaks and Scans; 3.2.5 Include a Time Dependent Stimulation; 4 Notes; References

Chapter 2: Using RuleBuilder to Graphically Define and Visua…