Extreme self-organization in networks constructed from gene expression data
Extreme self-organization in networks constructed from gene expression data
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DOI：
10.1103/physrevlett.89.268702
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发表时间：
2002-12-23
影响因子：
8.6
通讯作者：
Agrawal, H
中科院分区：
文献类型：
--
作者：
Agrawal, H
我们研究了从许多类型的癌症中获得的基因表达数据构建的网络。网络通过连接属于彼此的K个最近邻居的列表的顶点来构造，其中K是先验选择的非负整数。我们引入了一个序参数来表征网络的同质性。在最小化关于K的序参数时，网络的度分布在尾部表现出幂律行为，指数为1。网络的特征值谱分析证实了幂律和小世界行为的存在。我们讨论的背景下，进化的生物过程中，这些发现的意义。
We study networks constructed from gene expression data obtained from many types of cancers. The networks are constructed by connecting vertices that belong to each others' list of K nearest neighbors, with K being an a priori selected non-negative integer. We introduce an order parameter for characterizing the homogeneity of the networks. On minimizing the order parameter with respect to K, degree distribution of the networks shows power-law behavior in the tails with an exponent of unity. Analysis of the eigenvalue spectrum of the networks confirms the presence of the power-law and small-world behavior. We discuss the significance of these findings in the context of evolutionary biological processes.