RKappa: Software for Analyzing Rule-Based Models

Anatoly Sorokin; Oksana Sorokina; J. Douglas Armstrong

doi:10.1007/978-1-4939-9102-0_17

RKappa: Software for Analyzing Rule-Based Models

Anatoly Sorokin, Oksana Sorokina, J. Douglas Armstrong

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

RKappa is a framework for the development, simulation, and analysis of rule-based models within the mature statistically empowered R environment. It is designed for model editing, parameter identification, simulation, sensitivity analysis, and visualization. The framework is optimized for high-performance computing platforms and facilitates analysis of large-scale systems biology models where knowledge of exact mechanisms is limited and parameter values are uncertain.

Original language	English
Title of host publication	Modeling Biomolecular Site Dynamics: Methods and Protocols
Editors	William S. Hlavacek
Place of Publication	New York, NY
Publisher	Springer
Pages	363-390
Number of pages	28
ISBN (Print)	978-1-4939-9102-0
DOIs	https://doi.org/10.1007/978-1-4939-9102-0_17
Publication status	Published - 2019

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10.1007/978-1-4939-9102-0_17

https://link.springer.com/protocol/10.1007%2F978-1-4939-9102-0_17

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title = "RKappa: Software for Analyzing Rule-Based Models",

abstract = "RKappa is a framework for the development, simulation, and analysis of rule-based models within the mature statistically empowered R environment. It is designed for model editing, parameter identification, simulation, sensitivity analysis, and visualization. The framework is optimized for high-performance computing platforms and facilitates analysis of large-scale systems biology models where knowledge of exact mechanisms is limited and parameter values are uncertain.",

author = "Anatoly Sorokin and Oksana Sorokina and {Douglas Armstrong}, J.",

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AU - Sorokin, Anatoly

AU - Sorokina, Oksana

AU - Douglas Armstrong, J.

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AB - RKappa is a framework for the development, simulation, and analysis of rule-based models within the mature statistically empowered R environment. It is designed for model editing, parameter identification, simulation, sensitivity analysis, and visualization. The framework is optimized for high-performance computing platforms and facilitates analysis of large-scale systems biology models where knowledge of exact mechanisms is limited and parameter values are uncertain.

U2 - 10.1007/978-1-4939-9102-0_17

DO - 10.1007/978-1-4939-9102-0_17

M3 - Chapter

SN - 978-1-4939-9102-0

SP - 363

EP - 390

BT - Modeling Biomolecular Site Dynamics: Methods and Protocols

A2 - Hlavacek, William S.

PB - Springer

CY - New York, NY

ER -

RKappa: Software for Analyzing Rule-Based Models

Abstract

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