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The Mathematical Model of the Bcl-2 Family Mediated MOMP Regulation Can Perform a Non-Trivial Pattern Recognition

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Title
The Mathematical Model of the Bcl-2 Family Mediated MOMP Regulation Can Perform a Non-Trivial Pattern Recognition
Published in
PLOS ONE, December 2013
DOI 10.1371/journal.pone.0081861
Pubmed ID
Authors

Tomas Tokar, Jozef Ulicny

Abstract

Interactions between individual members of the B-cell lymphoma 2 (Bcl-2) family of proteins form a regulatory network governing mitochondrial outer membrane permeabilization (MOMP). Bcl-2 family initiated MOMP causes release of the inter-membrane pro-apoptotic proteins to cytosol and creates a cytosolic environment suitable for the executionary phase of apoptosis. We designed the mathematical model of this regulatory network where the synthesis rates of the Bcl-2 family members served as the independent inputs. Using computational simulations, we have then analyzed the response of the model to up-/downregulation of the Bcl-2 proteins. Under several assumptions, and using estimated reaction parameters, a non-linear stimulus-response emerged, whose characteristics are associated with bistability and switch-like behavior. Interestingly, using the principal component analysis (PCA) we have shown that the given model of the Bcl-2 family interactions classifies the random combinations of inputs into two distinct classes, and responds to these by one of the two qualitatively distinct outputs. As we showed, the emergence of this behavior requires specific organization of the interactions between particular Bcl-2 proteins.

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Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 30%
Researcher 4 20%
Student > Bachelor 3 15%
Unspecified 1 5%
Student > Master 1 5%
Other 1 5%
Unknown 4 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 35%
Biochemistry, Genetics and Molecular Biology 3 15%
Mathematics 2 10%
Psychology 2 10%
Immunology and Microbiology 1 5%
Other 1 5%
Unknown 4 20%