Approximating Attractors of Boolean Networks by Iterative CTL Model Checking.

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PyBoolNet: a python package for the generation, analysis and visualization of boolean networks.Griffin: A Tool for Symbolic Inference of Synchronous Boolean Molecular Networks.Target Control in Logical Models Using the Domain of Influence of Nodes.

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P2860

Approximating Attractors of Boolean Networks by Iterative CTL Model Checking.

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Approximating Attractors of Boolean Networks by Iterative CTL Model Checking.

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Approximating Attractors of Boolean Networks by Iterative CTL Model Checking.

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Approximating Attractors of Boolean Networks by Iterative CTL Model Checking.

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P1476

Approximating Attractors of Boolean Networks by Iterative CTL Model Checking.

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P2093

Hannes Klarner

http://www.w3.org/2001/XMLSchema#string

Heike Siebert

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P2860

Integrative modelling of the influence of MAPK network on cancer cell fate decision

Logical modelling of regulatory networks with GINsim 2.3.

Detection of attractors of large Boolean networks via exhaustive enumeration of appropriate subspaces of the state space.

Steady state analysis of Boolean molecular network models via model reduction and computational algebra.

Cell fate reprogramming by control of intracellular network dynamics.

Synchronous versus asynchronous modeling of gene regulatory networks.

An overview of existing modeling tools making use of model checking in the analysis of biochemical networks.

A SAT-based algorithm for finding attractors in synchronous Boolean networks.

Reduction of Boolean network models.

Analysis of discrete bioregulatory networks using symbolic steady states.

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130

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scholarly article

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10.3389/FBIOE.2015.00130

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2015-09-08T00:00:00Z

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282335243

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26442247

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P932

4562258

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Approximating Attractors of Boolean Networks by Iterative CTL Model Checking.

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P2860

P2860

Approximating Attractors of Boolean Networks by Iterative CTL Model Checking.

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type

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P1433

P1476

P2093

P2860

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P1476

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P5875

P698

P932