Reference : ON/OFF and beyond--a boolean model of apoptosis.
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/2067
ON/OFF and beyond--a boolean model of apoptosis.
English
Schlatter, Rebekka [> >]
Schmich, Kathrin [> >]
Avalos Vizcarra, Ima [> >]
Scheurich, Peter [> >]
Sauter, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >]
Borner, Christoph [> >]
Ederer, Michael [> >]
Merfort, Irmgard [> >]
Sawodny, Oliver [> >]
2009
PLoS Computational Biology
5
12
e1000595
Yes (verified by ORBilu)
1553-734X
1553-7358
United States
[en] Animals ; Apoptosis/radiation effects ; Computational Biology ; Humans ; Mice ; Models, Biological ; Signal Transduction
[en] Apoptosis is regulated by several signaling pathways which are extensively linked by crosstalks. Boolean or logical modeling has become a promising approach to capture the qualitative behavior of such complex networks. Here we built a large-scale literature-based Boolean model of the central intrinsic and extrinsic apoptosis pathways as well as pathways connected with them. The model responds to several external stimuli such as Fas ligand, TNF-alpha, UV-B irradiation, interleukin-1beta and insulin. Timescales and multi-value node logic were used and turned out to be indispensable to reproduce the behavior of the apoptotic network. The coherence of the model was experimentally validated. Thereby an UV-B dose-effect is shown for the first time in mouse hepatocytes. Analysis of the model revealed a tight regulation emerging from high connectivity and spanning crosstalks and a particular importance of feedback loops. An unexpected feedback from Smac release to RIP could further increase complex II formation. The introduced Boolean model provides a comprehensive and coherent description of the apoptosis network behavior. It gives new insights into the complex interplay of pro- and antiapoptotic factors and can be easily expanded to other signaling pathways.
http://hdl.handle.net/10993/2067
10.1371/journal.pcbi.1000595

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