The Effects of Feedback Loops on the Network Robustness by using a Random Boolean Network Model

랜덤 불리언 네트워크 모델을 이용한 되먹임 루프가 네트워크 강건성에 미치는 영향

  • 권영근 (울산대학교 컴퓨터정보통신공학부)
  • Received : 2009.08.17
  • Accepted : 2010.04.02
  • Published : 2010.06.15

Abstract

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.

생체네트워크는 여러 종류의 환경 변화에 매우 강건하다고 알려져 있지만 그 메커니즘은 아직 밝혀지지 않고 있다. 본 논문에서는 랜덤 네트워크에 비해 생체네트워크에 되먹임 루프가 매우 많이 존재한다는 구조적 특징을 발견하고 그것이 네트워크의 강건성에 어떤 영향을 미치는지를 살펴보았다. 이를 위해 불리언 네트워크 모델을 이용하여 네트워크 강건성을 적절하게 측정하는 방법을 정의하고 많은 불리언 네트워크에 대해서 시뮬레이션하였다. 그 결과, 불리언 네트워크에서 되먹임 루프의 개수가 증가하면 고정점 끌개의 개수는 거의 변화가 없지만 유한순환 끌개의 개수는 크게 줄어든다는 사실을 밝혔다. 또한, 되먹임 루프의 개수가 증가함에 따라 고정점 끌개로 수렴하는 거대한 끌개 영역이 생성됨을 보였다. 이러한 사실들은 매우 많은 수의 되먹임 루프가 네트워크의 강건성을 높이는 데 중요한 요인임을 설명한다.

Keywords

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