• Journal of KIISE:Computer Systems and Theory
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• v.37 no.3
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• pp.138-146
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• 2010

It is well known that many biological networks are very robust against various types of perturbations, but we still do not know the mechanism of robustness. In this paper, we find that there exist a number of feedback loops in a real biological network compared to randomly generated networks. Moreover, we investigate how the topological property affects network robustness. To this end, we properly define the notion of robustness based on a Boolean network model. Through extensive simulations, we show that the Boolean networks create a nearly constant number of fixed-point attractors, while they create a smaller number of limit-cycle attractors as they contain a larger number of feedback loops. In addition, we elucidate that a considerably large basin of a fixed-point attractor is generated in the networks with a large number of feedback loops. All these results imply that the existence of a large number of feedback loops in biological networks can be a critical factor for their robust behaviors.

• Bulletin of the Korean Mathematical Society
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• v.40 no.3
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• pp.465-473
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• 2003

Introducing the concept of a sequentially condensing operator in a more general framework, we give a new fixed point theorem for sequentially condensing operators in Banach spaces, with the aid of attractors.