Title :
Input-State Approach to Boolean Networks
Author_Institution :
Inst. of Syst. Sci., Chinese Acad. of Sci., Beijing
fDate :
3/1/2009 12:00:00 AM
Abstract :
This paper investigates the structure of Boolean networks via input-state structure. Using the algebraic form proposed by the author, the logic-based input-state dynamics of Boolean networks, called the Boolean control networks, is converted into an algebraic discrete-time dynamic system. Then the structure of cycles of Boolean control systems is obtained as compounded cycles. Using the obtained input-state description, the structure of Boolean networks is investigated, and their attractors are revealed as nested compounded cycles, called rolling gears. This structure explains why small cycles mainly decide the behaviors of cellular networks. Some illustrative examples are presented.
Keywords :
Boolean algebra; cellular neural nets; discrete time systems; graph theory; Boolean control networks; algebraic discrete-time dynamic system; cellular networks; logic-based input-state dynamics; rolling gears; Algebraic form; input-state structure; invariant subspace; network transition matrix; Algorithms; Genes; Logic; Neural Networks (Computer); Proteins; Signal Transduction;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2008.2011359