Document Type
Article
Publication Date
1-1-2011
Publication Title
Open Bioinformatics Journal
Volume
5
First Page
16
Last Page
25
Abstract
The use of modeling to observe and analyze the mechanisms of complex biochemical network function is becoming an important methodological tool in the systems biology era. Number of different approaches to model these networks have been utilized-- they range from analysis of static connection graphs to dynamical models based on kinetic interaction data. Dynamical models have a distinct appeal in that they make it possible to observe these networks in action, but they also pose a distinct challenge in that they require detailed information describing how the individual components of these networks interact in living cells. Because this level of detail is generally not known, dynamic modeling requires simplifying assumptions in order to make it practical. In this review Boolean modeling will be discussed, a modeling method that depends on the simplifying assumption that all elements of a network exist only in one of two states.
Recommended Citation
Helikar, Tomáš; Kochi, Naomi; Konvalina, John; and Rogers, Jim A., "Boolean Modeling of Biochemical Networks" (2011). Mathematics Faculty Publications. 57.
https://digitalcommons.unomaha.edu/mathfacpub/57
Comments
© Helikar et al.; Licensee Bentham Open. This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.