Extended Constraint-Based Boolean Analysis: A Computational Method in Genetic Network Inference

Reconstruction of a genetic network, which describes gene regulation of cellular response processes, has been widely studied by using various approaches. Some of which are computational expensive and require enormous efforts. Herein, we proposed an

extended

constraint-based Boolean

to infer genetic network. Our method incorporated the specific constraints for a particular system in addition to the general conceptual constraints of a typical genetic circuit, to improve the performance of the existing constraint-based Boolean algorithm. This method was demonstrated in inference of the genetic network underlying circadian rhythms from microarray time series data. The results showed that the proposed method provides good accuracy, specificity, and precision under the trade-off of computational efforts. Moreover, the resulting network showed that prior knowledge is a useful bias for modeling genetic network. The proposed method is therefore a promising alternative approach for inferring genetic network from high-throughput data, such as microarray.