Electronic Proceedings in Theoretical Computer Science · 2012 · 10 citations · 14 references
Life SciencesBiologySystems BiologyBiological Systems ModelingComputational BiologyNetwork BiologyBiological NetworksDynamic Systems ModelingNetwork DynamicsNetwork ModelingComplex Network AnalysisComplex Network TheoryHybrid Dynamical SystemsIron Homeostasis RegulationNetwork-based Modeling
This paper presents a novel framework for the modeling of biological networks. It makes use of recent tools analyzing the robust satisfaction of properties of (hybrid) dynamical systems. The main challenge of this approach as applied to biological systems is to get access to the relevant parameter sets despite gaps in the available knowledge. An initial estimate of useful parameters was sought by formalizing the known behavior of the biological network in the STL logic using the tool Breach. Then, once a set of parameter values consistent with known biological properties was found, we tried to locally expand it into the largest possible valid region. We applied this methodology in an effort to model and better understand the complex network regulating iron homeostasis in mammalian cells. This system plays an important role in many biological functions, including erythropoiesis, resistance against infections, and proliferation of cancer cells.
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Mitchell D. Knutson, Mohamed Oukka, Lindsey M. Koss et al. · Proceedings of the National Academy of Sciences · 2005 · 481 citations · Full text
Fluorescence Analysis of the Labile Iron Pool of Mammalian Cells
Silvina Epsztejn, Or Kakhlon, Hava Glickstein et al. · Analytical Biochemistry · 1997 · 392 citations
A new syndrome of liver iron overload with normal transferrin saturation
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Medicine, Biochemistry, Hematology +16
Laurent Granvilliers, Frédéric Benhamou · ACM Transactions on Mathematical Software · 2006 · 228 citations