Article (Scientific journals)
ON/OFF and beyond--a boolean model of apoptosis.
Schlatter, Rebekka; Schmich, Kathrin; Avalos Vizcarra, Ima et al.
2009In PLoS Computational Biology, 5 (12), p. 1000595
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Keywords :
Animals; Apoptosis/radiation effects; Computational Biology; Humans; Mice; Models, Biological; Signal Transduction
Abstract :
[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.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
Schlatter, Rebekka
Schmich, Kathrin
Avalos Vizcarra, Ima
Scheurich, Peter
Sauter, Thomas ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Borner, Christoph
Ederer, Michael
Merfort, Irmgard
Sawodny, Oliver
Language :
English
Title :
ON/OFF and beyond--a boolean model of apoptosis.
Publication date :
2009
Journal title :
PLoS Computational Biology
ISSN :
1553-7358
Publisher :
Public Library of Science, United States - California
Volume :
5
Issue :
12
Pages :
e1000595
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBilu :
since 23 May 2013

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