Dynamics of Cell Fate Decision Mediated by the Interplay of Autophagy and Apoptosis in Cancer Cells Mathematical Modeling and Experimental Observations /

This interdisciplinary thesis introduces a systems biology approach to study the cell fate decision mediated by autophagy. A mathematical model of interaction between Autophagy and Apoptosis in mammalian cells is proposed. In this dynamic model autophagy acts as a gradual response to stress (Rheosta...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Tavassoly, Iman (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2015.
Σειρά:Springer Theses, Recognizing Outstanding Ph.D. Research,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Dynamics of Cell Fate Decision Mediated by the Interplay of Autophagy and Apoptosis in Cancer Cells  |h [electronic resource] :  |b Mathematical Modeling and Experimental Observations /  |c by Iman Tavassoly. 
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505 0 |a Introduction -- Mathematical Modeling of the Interplay of Autophagy and Apoptosis -- An Experimental Framework to Study the Dynamics of Autophagic Response -- Conclusions -- Source Code. 
520 |a This interdisciplinary thesis introduces a systems biology approach to study the cell fate decision mediated by autophagy. A mathematical model of interaction between Autophagy and Apoptosis in mammalian cells is proposed. In this dynamic model autophagy acts as a gradual response to stress (Rheostat) that delays the initiation of bistable switch of apoptosis to give the cells an opportunity to survive. The author shows that his dynamical model is consistent with existing quantitative measurements of time courses of autophagic responses to cisplatin treatment. To understand the function of this response in cancer cells, he has provided a systems biology experimental framework to study quantitative and dynamical aspects of autophagy in single cancer cells using live-cell imaging and quantitative fluorescence microscopy. This framework can provide new insights on function of autophagic response in cancer cells. 
650 0 |a Materials science. 
650 0 |a Cancer research. 
650 0 |a Bioinformatics. 
650 0 |a Cell biology. 
650 0 |a Biophysics. 
650 0 |a Biological physics. 
650 0 |a Biomaterials. 
650 1 4 |a Materials Science. 
650 2 4 |a Biomaterials. 
650 2 4 |a Computational Biology/Bioinformatics. 
650 2 4 |a Cancer Research. 
650 2 4 |a Cell Biology. 
650 2 4 |a Biophysics and Biological Physics. 
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