Ito Sohei, Ichinose Takuma, Shimakawa Masaya, Izumi Naoko, Hagihara Shigeki, Yonezaki Naoki
The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.
J Integr Bioinform. 2013 Mar 25;10(2):216. doi: 10.2390/biecoll-jib-2013-216.
Despite a lot of advances in biology and genomics, it is still difficult to utilise such valuable knowledge and information to understand and analyse large biological systems due to high computational complexity. In this paper we propose a modular method with which from several small network analyses we analyse a large network by integrating them. This method is based on the qualitative framework proposed by authors in which an analysis of gene networks is reduced to checking satisfiability of linear temporal logic formulae. The problem of linear temporal logic satisfiability checking needs exponential time in the size of a formula. Thus it is difficult to analyse large networks directly in this method since the size of a formula grows linearly to the size of a network. The modular method alleviates this computational difficulty. We show some experimental results and see how we benefit from the modular analysis method.
尽管生物学和基因组学取得了诸多进展,但由于计算复杂度高,利用这些宝贵的知识和信息来理解和分析大型生物系统仍然困难。在本文中,我们提出了一种模块化方法,通过整合多个小型网络分析来分析大型网络。该方法基于作者提出的定性框架,其中基因网络分析被简化为检查线性时态逻辑公式的可满足性。线性时态逻辑可满足性检查问题在公式规模上需要指数时间。因此,由于公式规模与网络规模呈线性增长,直接用这种方法分析大型网络很困难。模块化方法缓解了这种计算难题。我们展示了一些实验结果,并看看如何从模块化分析方法中受益。