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  ALC : automated reduction of rule-based models

Koschorreck, M., & Gilles, E. D. (2008). ALC: automated reduction of rule-based models. BMC Systems Biology, 2: 91. doi:10.1186/1752-0509-2-91.

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© 2008 Koschorreck and Gilles; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Koschorreck, M.1, Author           
Gilles, E. D.1, Author           
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1Systems Biology, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738155              

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 Abstract: Background Combinatorial complexity is a challenging problem for the modeling of cellular signal transduction since the association of a few proteins can give rise to an enormous amount of feasible protein complexes. The layer-based approach is an approximative, but accurate method for the mathematical modeling of signaling systems with inherent combinatorial complexity. The number of variables in the simulation equations is highly reduced and the resulting dynamic models show a pronounced modularity. Layer-based modeling allows for the modeling of systems not accessible previously. Results ALC (Automated Layer Construction) is a computer program that highly simplifies the building of reduced modular models, according to the layer-based approach. The model is defined using a simple but powerful rule-based syntax that supports the concepts of modularity and macrostates. ALC performs consistency checks on the model definition and provides the model output in different formats (C MEX, MATLAB, Mathematica and SBML) as ready-to-run simulation files. ALC also provides additional documentation files that simplify the publication or presentation of the models. The tool can be used offline or via a form on the ALC website. Conclusions ALC allows for a simple rule-based generation of layer-based reduced models. The model files are given in different formats as ready-to-run simulation files. © 2008 Koschorreck and Gilles, licensee BioMed Central Ltd. [accessed December 17, 2008]

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Language(s): eng - English
 Dates: 2008
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: eDoc: 395957
Other: 23/08
DOI: 10.1186/1752-0509-2-91
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Title: BMC Systems Biology
Source Genre: Journal
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Pages: - Volume / Issue: 2 Sequence Number: 91 Start / End Page: - Identifier: -