Title |
ON/OFF and Beyond - A Boolean Model of Apoptosis
|
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Published in |
PLoS Computational Biology, December 2009
|
DOI | 10.1371/journal.pcbi.1000595 |
Pubmed ID | |
Authors |
Rebekka Schlatter, Kathrin Schmich, Ima Avalos Vizcarra, Peter Scheurich, Thomas Sauter, Christoph Borner, Michael Ederer, Irmgard Merfort, Oliver Sawodny |
Abstract |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 8 | 4% |
United States | 6 | 3% |
France | 2 | 1% |
United Kingdom | 2 | 1% |
Portugal | 1 | <1% |
Norway | 1 | <1% |
Sweden | 1 | <1% |
Romania | 1 | <1% |
Luxembourg | 1 | <1% |
Other | 0 | 0% |
Unknown | 157 | 87% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 51 | 28% |
Researcher | 43 | 24% |
Student > Master | 25 | 14% |
Professor > Associate Professor | 11 | 6% |
Student > Bachelor | 10 | 6% |
Other | 29 | 16% |
Unknown | 11 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 85 | 47% |
Computer Science | 21 | 12% |
Biochemistry, Genetics and Molecular Biology | 18 | 10% |
Engineering | 12 | 7% |
Medicine and Dentistry | 7 | 4% |
Other | 20 | 11% |
Unknown | 17 | 9% |