Difference between revisions of "Modeling extrinsic fluctuations with StochPy"

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|Contact person2=Timo Maarleveld
 
|Contact person2=Timo Maarleveld
 
|Contact person3=Anne Schwabe
 
|Contact person3=Anne Schwabe
|Master areas=Bioinformatics, Systems Biology
 
 
|Fulfilled=No
 
|Fulfilled=No
 
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Single-cell and single-molecule measurements indicate the importance of stochastic phenomena in cell biology. Stochasticity creates spontaneous differences in the copy numbers of key macromolecules and the timing of reaction events between genetically-identical cells. Mathematical models are indispensable for the study of phenotypic stochasticity in cellular decision-making and cell survival. There is a demand for versatile, stochastic modeling environments with extensive, preprogrammed statistics functions and plotting capabilities that hide the mathematics from the novice users and offers low-level programming access to the experienced user. Hence, we recently developed StochPy (Stochastic modeling in Python), which is a flexible software tool for stochastic simulation in cell biology. Our tool allows novice and experienced users to study stochastic phenomena in cell biology. The integration with other Python software makes StochPy both a user-friendly and easily extendible simulation tool.
 
Single-cell and single-molecule measurements indicate the importance of stochastic phenomena in cell biology. Stochasticity creates spontaneous differences in the copy numbers of key macromolecules and the timing of reaction events between genetically-identical cells. Mathematical models are indispensable for the study of phenotypic stochasticity in cellular decision-making and cell survival. There is a demand for versatile, stochastic modeling environments with extensive, preprogrammed statistics functions and plotting capabilities that hide the mathematics from the novice users and offers low-level programming access to the experienced user. Hence, we recently developed StochPy (Stochastic modeling in Python), which is a flexible software tool for stochastic simulation in cell biology. Our tool allows novice and experienced users to study stochastic phenomena in cell biology. The integration with other Python software makes StochPy both a user-friendly and easily extendible simulation tool.
  
 
Although the intrinsic stochasticity inherent in biochemistry is relatively well understood, cellular variation, or ‘noise’, is predominantly generated by interactions of the system of interest with other stochastic systems in the cell or its environment. Such extrinsic fluctuations are nonspecific, affecting many system components, and have a substantial lifetime, comparable to the cell cycle.  In this project, we want extend StochPy's stochastic simulation algorithms to include these extrinsic fluctuations.
 
Although the intrinsic stochasticity inherent in biochemistry is relatively well understood, cellular variation, or ‘noise’, is predominantly generated by interactions of the system of interest with other stochastic systems in the cell or its environment. Such extrinsic fluctuations are nonspecific, affecting many system components, and have a substantial lifetime, comparable to the cell cycle.  In this project, we want extend StochPy's stochastic simulation algorithms to include these extrinsic fluctuations.

Latest revision as of 10:09, 24 August 2016


About Modeling extrinsic fluctuations with StochPy


Description

|free text=}} Single-cell and single-molecule measurements indicate the importance of stochastic phenomena in cell biology. Stochasticity creates spontaneous differences in the copy numbers of key macromolecules and the timing of reaction events between genetically-identical cells. Mathematical models are indispensable for the study of phenotypic stochasticity in cellular decision-making and cell survival. There is a demand for versatile, stochastic modeling environments with extensive, preprogrammed statistics functions and plotting capabilities that hide the mathematics from the novice users and offers low-level programming access to the experienced user. Hence, we recently developed StochPy (Stochastic modeling in Python), which is a flexible software tool for stochastic simulation in cell biology. Our tool allows novice and experienced users to study stochastic phenomena in cell biology. The integration with other Python software makes StochPy both a user-friendly and easily extendible simulation tool.

Although the intrinsic stochasticity inherent in biochemistry is relatively well understood, cellular variation, or ‘noise’, is predominantly generated by interactions of the system of interest with other stochastic systems in the cell or its environment. Such extrinsic fluctuations are nonspecific, affecting many system components, and have a substantial lifetime, comparable to the cell cycle. In this project, we want extend StochPy's stochastic simulation algorithms to include these extrinsic fluctuations.