Scalable steady state analysis of Boolean biological regulatory networks.
BACKGROUND
Computing the long term behavior of regulatory and signaling networks is critical in understanding how biological functions take place in organisms. Steady states of these networks determine the activity levels of individual entities in the long run. Identifying all the steady states of these networks is difficult due to the state space explosion problem.


METHODS
In this paper, we propose a method for identifying all the steady states of Boolean regulatory and signaling networks accurately and efficiently. We build a mathematical model that allows pruning a large portion of the state space quickly without causing any false dismissals. For the remaining state space, which is typically very small compared to the whole state space, we develop a randomized traversal method that extracts the steady states. We estimate the number of steady states, and the expected behavior of individual genes and gene pairs in steady states in an online fashion. Also, we formulate a stopping criterion that terminates the traversal as soon as user supplied percentage of the results are returned with high confidence.


CONCLUSIONS
This method identifies the observed steady states of boolean biological networks computationally. Our algorithm successfully reported the G1 phases of both budding and fission yeast cell cycles. Besides, the experiments suggest that this method is useful in identifying co-expressed genes as well. By analyzing the steady state profile of Hedgehog network, we were able to find the highly co-expressed gene pair GL1-SMO together with other such pairs.


BACKGROUND
Source code of this work is available at http://bioinformatics.cise.ufl.edu/palSteady.html twocolumnfalse].
Ay
Ferhat
F
Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, United States of America. fay@cise.ufl.edu
Xu
Fei
F
Kahveci
Tamer
T
D000465:Algorithms; D002453:Cell Cycle / Q000235:genetics; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks / Q000235:genetics*; D053823:Hedgehog Proteins / Q000235:genetics / Q000378:metabolism; D006801:Humans; D008957:Models, Genetic; D004718:Saccharomycetales / Q000166:cytology / Q000235:genetics; D012568:Schizosaccharomyces / Q000166:cytology / Q000235:genetics
D053823:Hedgehog Proteins