With the rise of systems biology as an important paradigm in the life sciences and the availability and increasingly good quality of high-throughput molecular data, the role of mathematical models has become central in the understanding of the relationship between structure and function of organisms. This chapter focuses on a particular type of models, so-called algebraic models, which are generalizations of Boolean networks. It provides examples of such models and discusses several available methods to construct such models from high-throughput time course data. One specific such method, Polynome, is discussed in detail.
%0 Journal Article
%1 Laubenbacher2009Algebraic
%A Laubenbacher, Reinhard
%A Jarrah, Abdul Salam S.
%D 2009
%J Methods in enzymology
%K boolean mathematical-models systems-biology
%P 163--196
%R 10.1016/s0076-6879(09)67007-5
%T Algebraic models of biochemical networks.
%U http://dx.doi.org/10.1016/s0076-6879(09)67007-5
%V 467
%X With the rise of systems biology as an important paradigm in the life sciences and the availability and increasingly good quality of high-throughput molecular data, the role of mathematical models has become central in the understanding of the relationship between structure and function of organisms. This chapter focuses on a particular type of models, so-called algebraic models, which are generalizations of Boolean networks. It provides examples of such models and discusses several available methods to construct such models from high-throughput time course data. One specific such method, Polynome, is discussed in detail.
@article{Laubenbacher2009Algebraic,
abstract = {With the rise of systems biology as an important paradigm in the life sciences and the availability and increasingly good quality of high-throughput molecular data, the role of mathematical models has become central in the understanding of the relationship between structure and function of organisms. This chapter focuses on a particular type of models, so-called algebraic models, which are generalizations of Boolean networks. It provides examples of such models and discusses several available methods to construct such models from high-throughput time course data. One specific such method, Polynome, is discussed in detail.},
added-at = {2018-12-02T16:09:07.000+0100},
author = {Laubenbacher, Reinhard and Jarrah, Abdul Salam S.},
biburl = {https://www.bibsonomy.org/bibtex/2841fdbdfac0f1a53aa40ca5df2a4114f/karthikraman},
citeulike-article-id = {6097190},
citeulike-linkout-0 = {http://dx.doi.org/10.1016/s0076-6879(09)67007-5},
citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/19897093},
citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=19897093},
doi = {10.1016/s0076-6879(09)67007-5},
interhash = {c0ade88588c1b88bc29cb50c43b68674},
intrahash = {841fdbdfac0f1a53aa40ca5df2a4114f},
issn = {1557-7988},
journal = {Methods in enzymology},
keywords = {boolean mathematical-models systems-biology},
pages = {163--196},
pmid = {19897093},
posted-at = {2009-11-11 09:28:57},
priority = {4},
timestamp = {2018-12-02T16:09:07.000+0100},
title = {Algebraic models of biochemical networks.},
url = {http://dx.doi.org/10.1016/s0076-6879(09)67007-5},
volume = 467,
year = 2009
}