Mustafa Khammash
- Published in print:
- 2009
- Published Online:
- August 2013
- ISBN:
- 9780262013345
- eISBN:
- 9780262258906
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262013345.003.0002
- Subject:
- Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies
This chapter introduces types of stochastic modeling used to address the probabilistic nature of processes. It reviews some of the key approaches for this modeling and considers the analysis of ...
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This chapter introduces types of stochastic modeling used to address the probabilistic nature of processes. It reviews some of the key approaches for this modeling and considers the analysis of cellular noise and the resulting fluctuations in the copy numbers of cellular constituents. It addresses the origins and implications of noise in biological networks. It then describes the stochastic framework for modeling chemical reactions and provides a link between stochastic and deterministic descriptions. This chapter shows that the density computation methods are especially suitable for very low molecule counts, moment closure methods for medium to large counts, and the linear noise approximation for very large counts.Less
This chapter introduces types of stochastic modeling used to address the probabilistic nature of processes. It reviews some of the key approaches for this modeling and considers the analysis of cellular noise and the resulting fluctuations in the copy numbers of cellular constituents. It addresses the origins and implications of noise in biological networks. It then describes the stochastic framework for modeling chemical reactions and provides a link between stochastic and deterministic descriptions. This chapter shows that the density computation methods are especially suitable for very low molecule counts, moment closure methods for medium to large counts, and the linear noise approximation for very large counts.
