Jimena: efficient computing and system state identification for genetic regulatory networks.

ABSTRACT:

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) co

SUBMITTER: Karl S 

PROVIDER: S-EPMC3853020 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature