摘要翻译：
我们提出了一种预测顶点函数的一般方法，其中：1。网络的布线在某种程度上与顶点功能有关。2.对部分顶点进行了功能分类。该方法受社会网络分析中角色相似性度量的影响。我们的两个版本的预测方案在模型网络上测试，顶点的功能被设计为匹配其网络环境。我们还将这些方法应用于酵母的蛋白质组，并发现结果与更专业的方法相一致。
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英文标题：
《Role-similarity based functional prediction in networked systems:
  Application to the yeast proteome》
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作者：
Petter Holme and Mikael Huss
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最新提交年份：
2005
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Molecular Networks        分子网络
分类描述：Gene regulation, signal transduction, proteomics, metabolomics, gene and enzymatic networks
基因调控、信号转导、蛋白质组学、代谢组学、基因和酶网络
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一级分类：Physics        物理学
二级分类：Other Condensed Matter        其他凝聚态物质
分类描述：Work in condensed matter that does not fit into the other cond-mat classifications
在不适合其他cond-mat分类的凝聚态物质中工作
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一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
  We propose a general method to predict functions of vertices where: 1. The wiring of the network is somehow related to the vertex functionality. 2. A fraction of the vertices are functionally classified. The method is influenced by role-similarity measures of social network analysis. The two versions of our prediction scheme is tested on model networks were the functions of the vertices are designed to match their network surroundings. We also apply these methods to the proteome of the yeast Saccharomyces cerevisiae and find the results compatible with more specialized methods.
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PDF链接：
https://arxiv.org/pdf/q-bio/0503010