Akutsu T, Miyano S, Kuhara S
Human Genome Center, University of Tokyo, Japan.
Pac Symp Biocomput. 2000:293-304. doi: 10.1142/9789814447331_0028.
Modeling genetic networks and metabolic networks is an important topic in bioinformatics. We propose a qualitative network model which is a combination of the Boolean network and qualitative reasoning, where qualitative reasoning is a kind of reasoning method well-studied in Artificial Intelligence. We also present algorithms for inferring qualitative networks from time series data and an algorithm for inferring S-systems (synergistic and saturable systems) from time series data, where S-systems are based on a particular kind of nonlinear differential equation and have been applied to the analysis of various biological systems.
对遗传网络和代谢网络进行建模是生物信息学中的一个重要课题。我们提出了一种定性网络模型，它是布尔网络和定性推理的结合，而定性推理是人工智能中一种经过充分研究的推理方法。我们还给出了从时间序列数据推断定性网络的算法，以及从时间序列数据推断S-系统（协同和饱和系统）的算法，其中S-系统基于一种特定类型的非线性微分方程，并已应用于各种生物系统的分析。
