BoolNet—an R package for generation, reconstruction and analysis of Boolean networks | Zendy

Christoph Müssel | Zendy; Martin Hopfensitz | Zendy; Hans A. Kestler | Zendy

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BoolNet—an R package for generation, reconstruction and analysis of Boolean networks

Author(s) -

Christoph Müssel,

Martin Hopfensitz,

Hans A. Kestler

Publication year - 2010

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btq124

Subject(s) - computer science , probabilistic logic , preprocessor , asynchronous communication , theoretical computer science , sbml , biological network , mit license , implementation , robustness (evolution) , markov chain , visualization , gene regulatory network , data mining , artificial intelligence , license , machine learning , software engineering , computational biology , computer network , biochemistry , chemistry , gene expression , markup language , xml , biology , operating system , gene

As the study of information processing in living cells moves from individual pathways to complex regulatory networks, mathematical models and simulation become indispensable tools for analyzing the complex behavior of such networks and can provide deep insights into the functioning of cells. The dynamics of gene expression, for example, can be modeled with Boolean networks (BNs). These are mathematical models of low complexity, but have the advantage of being able to capture essential properties of gene-regulatory networks. However, current implementations of BNs only focus on different sub-aspects of this model and do not allow for a seamless integration into existing preprocessing pipelines.

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