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Evolving Sensitivity Balances Boolean Networks Jamie X. Luo1,2, Matthew S. Turner1,2* 1 Centre for Complexity Science, University of Warwick, Coventry, West Midlands, United Kingdom, 2 Department of Physics, University o
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Document Date: 2012-05-15 15:28:54

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Evolving Sensitivity Balances Boolean Networks / Gould / Boolean Networks / MIT Press / Threshold Boolean Networks / Evolved Networks / matrix sA / Ge / robustness sA / Gene Regulatory Networks / Oxford University Press / Winn AE / Evolving Sensitivity Balances Boolean Networks networks / Hupp / Creative Commons / Kauffman SA / /

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Technical University of Madrid / University of Warwick / /

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genetic regulatory networks / differential equation networks / daughter networks / interaction network / biological systems / gene network / cases networks / stem cell networks / regulatory networks / research tool / evolutionary algorithms / reagents/ materials/analysis tools / yeast cell-cycle network / stochastic differential equation systems / finite systems / insilico genetic networks / genetic networks / time systems / regulatory network / genetic switch systems / computing / evolutionary search / cell differentiation networks / balanced networks / random networks / biochemical networks / /

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Technical University of Madrid / Centre for Complexity Science / MIT / Department of Physics / National Academy of Sciences / Engineering and Physical Sciences Research Council / University of Warwick / Oxford University / Royal Society / Molecular Biology Intelligence Unit / /

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Hakim V / Artificial Life / /

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California / /

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Current Opinion / Condensed Matter / Proceedings of the National Academy of Sciences / PLoS ONE / Proceedings of the Royal Society / Journal of Theoretical Biology / Complex Systems / Molecular Biology / Molecular Systems Biology / /

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Av / The algorithm / stem cells / apoptosis / gene expression / Simulation / relating pluripotent stem cells / /

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