12867
2013
eng
14
article
1
2016-03-04
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Jimena: Efficient computing and system state identification for genetic regulatory networks
Background: Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed.
Results: (i) As a part of our new GRN simulation framework Jimena we introduce and setup Boolean-tree-based data structures; (ii) corresponding algorithms greatly expedite the calculation of the polynomial interpolation in almost all cases, thereby expanding the range of networks which can be simulated by this model in reasonable time. (iii) Stable states for discrete models are efficiently counted and identified using binary decision diagrams. As application example, we show how system states can now be sampled efficiently in small up to large scale hormone disease networks (Arabidopsis thaliana development and immunity, pathogen Pseudomonas syringae and modulation by cytokinins and plant hormones).
Conclusions: Jimena simulates currently available GRNs about 10-100 times faster than the previous implementation of the polynomial interpolation model and even greater gains are achieved for large scale-free networks. This speed-up also facilitates a much more thorough sampling of continuous state spaces which may lead to the identification of new stable states. Mutants of large networks can be constructed and analyzed very quickly enabling new insights into network robustness and behavior.
BMC Bioinformatics
10.1186/1471-2105-14-306
urn:nbn:de:bvb:20-opus-128671
BMC Bioinformatics 2013, 14:306. doi:10.1186/1471-2105-14-306
Stefan Karl
Thomas Dandekar
eng
uncontrolled
Boolean function
eng
uncontrolled
genetic regulatory network
eng
uncontrolled
interpolation
eng
uncontrolled
stable state
eng
uncontrolled
binary decision diagram
eng
uncontrolled
Boolean tree
Datenverarbeitung; Informatik
Biowissenschaften; Biologie
open_access
Theodor-Boveri-Institut für Biowissenschaften
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/12867/011_Karl_Jimena.pdf