Gowda Tejaswi, Vrudhula Sarma, Kim Seungchan
School of Computing and Informatics, Arizona State University, Tempe, Arizona, USA.
Ann N Y Acad Sci. 2009 Mar;1158:276-86. doi: 10.1111/j.1749-6632.2008.03763.x.
The two important problems of computational biology are the modeling of gene regulatory networks and the study of the network structure of complex biological systems. There is an increased use of mathematical and computational theory techniques to solve both these problems. The Boolean circuit model is one of the most popular modeling paradigms used to model gene regulatory networks. In this paper we try to make use of the properties of threshold logic (an alternative to Boolean logic to design digital circuits) to determine the network structure of gene systems. This approach uses the gene-expression data from microarray experiments as input. The proposed method was first used to build the gene network for a set of genes, proteins, and other molecular components based on in silico data. Then, the method was applied to a biological dataset to build the gene regulatory network for a core set of genes associated with melanoma. Some of the interactions found could be verified by earlier biological experiments reported in published literature. Other interactions that could not be validated by existing biological knowledge can provide insights into the investigation of bio-chemical pathways associated with melanoma development.
计算生物学的两个重要问题是基因调控网络的建模以及复杂生物系统的网络结构研究。为了解决这两个问题，数学和计算理论技术的应用越来越多。布尔电路模型是用于基因调控网络建模的最流行的建模范式之一。在本文中，我们尝试利用阈值逻辑（设计数字电路时替代布尔逻辑的一种方法）的特性来确定基因系统的网络结构。这种方法将来自微阵列实验的基因表达数据用作输入。所提出的方法首先基于计算机模拟数据为一组基因、蛋白质和其他分子成分构建基因网络。然后，该方法应用于一个生物数据集，为与黑色素瘤相关的一组核心基因构建基因调控网络。一些发现的相互作用可以通过已发表文献中报道的早期生物学实验得到验证。其他无法通过现有生物学知识验证的相互作用可以为与黑色素瘤发展相关的生化途径研究提供见解。
