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Modeling Biomolecular Site Dynamics

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Cover of 'Modeling Biomolecular Site Dynamics'

Table of Contents

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    Book Overview
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    Chapter 1 A Pycellerator Tutorial
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    Chapter 2 Using RuleBuilder to Graphically Define and Visualize BioNetGen-Language Patterns and Reaction Rules
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    Chapter 3 Strategy-Driven Exploration for Rule-Based Models of Biochemical Systems with Porgy
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    Chapter 4 Using rxncon to Develop Rule-Based Models
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    Chapter 5 Efficiently Encoding Complex Biochemical Models with the Multistate Model Builder (MSMB)
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    Chapter 6 Multi-Level Modeling and Simulation of Cellular Systems: An Introduction to ML-Rules
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    Chapter 7 Using Python for Spatially Resolved Modeling with Simmune
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    Chapter 8 Rule-Based Modeling Using Wildcards in the Smoldyn Simulator
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    Chapter 9 MCell-R: A Particle-Resolution Network-Free Spatial Modeling Framework
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    Chapter 10 Spatial Rule-Based Simulations: The SRSim Software
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    Chapter 11 CellOrganizer: Learning and Using Cell Geometries for Spatial Cell Simulations
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    Chapter 12 Using Mechanistic Models for Analysis of Proteomic Data
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    Chapter 13 Annotations for Rule-Based Models
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    Chapter 14 Markov Chain Aggregation and Its Application to Rule-Based Modelling
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    Chapter 15 In Silico Evolution of Signaling Networks Using Rule-Based Models: Bistable Response Dynamics
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    Chapter 16 Recipes for Analysis of Molecular Networks Using the Data2Dynamics Modeling Environment
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    Chapter 17 RKappa: Software for Analyzing Rule-Based Models
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    Chapter 18 A Step-by-Step Guide to Using BioNetFit
Attention for Chapter 15: In Silico Evolution of Signaling Networks Using Rule-Based Models: Bistable Response Dynamics
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Chapter title
In Silico Evolution of Signaling Networks Using Rule-Based Models: Bistable Response Dynamics
Chapter number 15
Book title
Modeling Biomolecular Site Dynamics
Published by
Humana Press, New York, NY, January 2019
DOI 10.1007/978-1-4939-9102-0_15
Pubmed ID
Book ISBNs
978-1-4939-9100-6, 978-1-4939-9102-0
Authors

Song Feng, Orkun S. Soyer, Feng, Song, Soyer, Orkun S.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 33%
Researcher 1 33%
Other 1 33%
Readers by discipline Count As %
Physics and Astronomy 2 67%
Biochemistry, Genetics and Molecular Biology 1 33%