Modeling Biomolecular Site Dynamics: Methods and Protocols

ISBN-13: 9781493991006 / Angielski / Twarda / 2019 / 423 str.

Hlavacek, William S.

Opis

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.

Spis treści

Preface…

Foreword…

Table of Contents…

Contributing Authors…

1. A Pycellerator Tutorial

Bruce E. Shapiro and Eric Mjolsness

2. Using RuleBuilder to Graphically Define and Visualize BioNetGen-Language Patterns and Reaction Rules

Ryan Suderman, G. Matthew Fricke, and William S. Hlavacek

3. Strategy-Driven Exploration for Rule-Based Models of Biochemical Systems with PORGY

Oana Andrei, Maribel Fernández, Hélène Kirchner, and Bruno Pinaud

4. Using rxncon to Develop Rule-Based Models

Jesper Romers, Sebastian Thieme, Ulrike Münzner, and Marcus Krantz

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

Alida Palmisano, Stefan Hoops, Layne T. Watson, Thomas C. Jones, Jr., John J. Tyson and Clifford A. Shaffer

6. Multi-Level Modeling and Simulation of Cellular Systems: An Introduction to ML-Rules

Tobias Helms, Tom Warnke, and Adelinde M. Uhrmacher

7. Using Python for Spatially Resolved Modeling with Simmune

Bastian R. Angermann and Martin Meier-Schellersheim

8. Rule-Based Modeling using Wildcards in the Smoldyn Simulator

Steven S. Andrews

9. MCell-R: A Particle-Resolution Network-Free Spatial Modeling Framework

Jose-Juan Tapia, Ali Sinan Saglam, Jacob Czech, Robert Kuczewski, Thomas M. Bartol, Terrence J. Sejnowski, and James R. Faeder

10. Spatial Rule-Based Simulations: the SRSim Software

Richard Henze, Gerd Grünert, Bashar Ibrahim, and Peter Dittrich

11. CellOrganizer: Learning and Using Cell Geometries for Spatial Cell Simulations

Timothy D. Majarian, Ivan Cao-Berg, Xiongtao Ruan, and Robert F. Murphy

12. Using Mechanistic Models for Analysis of Proteomic Data

Lily A. Chylek

13. Annotations for Rule-Based Models

Matteo Cavaliere, Vincent Danos, Ricardo Honorato-Zimmer, and William Waites

14. Markov Chain Aggregation and Its Application to Rule-Based Modelling

Tatjana Petrov

15. In Silico Evolution of Signaling Networks Using Rule-Based Models: Bistable Response Dynamics

Song Feng and Orkun S. Soyer

16. Recipes for Analysis of Molecular Networks Using the Data2Dynamics Modeling Environment

Bernhard Steiert, Clemens Kreutz, Andreas Raue, and Jens Timmer

17. RKappa: Software for Analyzing Rule-Based Models

Anatoly Sorokin, Oksana Sorokina, and J. Douglas Armstrong

18. A Step-by-Step Guide to Using BioNetFit

William S. Hlavacek, Jennifer Longo, Lewis R. Baker, María del Carmen Ramos Álamo, Alexander Ionkov, Eshan D. Mitra, Ryan Suderman, Keesha E. Erickson, Raquel Dias, Joshua Colvin, Brandon R. Thomas, and Richard G. Posner