Shared relationship analysis: ranking set cohesion and commonalities within a literature-derived relationship network
Shared relationship analysis: ranking set cohesion and commonalities within a literature-derived relationship network
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DOI：
10.1093/bioinformatics/btg390
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发表时间：
2004-01-22
期刊：
影响因子：
5.8
通讯作者：
Garner, HR
中科院分区：
文献类型：
--
作者：
Wren, JD;Garner, HR
动机：有一个普遍的科学需要，能够识别和评估任何给定的一组“对象”（例如基因，表型，化学品，疾病）有什么共同之处。无论是分类，扩大或识别共性和功能分组，信息需求可以是多种多样的，最好的来源，以确定一个潜在的异质性的一组对象之间的关系是科学literature.Results：我们首先建立一个网络的相关对象的共同出现在MEDLINE记录。然后，可以查询该网络中的一组对象以识别共享关系，并提出一种方法，通过将观察到的频率与随机网络模型中的预期频率进行比较来对其统计相关性进行评分。使用基因本体（GO）类别，我们证明了这种方法能够对一组对象的“内聚性”进行定量排名，并且重要的是，允许识别和评估与该组相关的其他对象的“内聚性”。补充信息：与分析的每个GO类别相关的排名基因列表可以在http://innovation.swmed.edu/IRIDESCENT/GO_relationships.htm上找到
Motivation: There is a general scientific need to be able to identify and evaluate what any given set of 'objects' (e.g. genes, phenotypes, chemicals, diseases) has in common. Whether it is to classify, expand upon or identify commonalities and functional groupings, informational needs can be diverse and the best source to identify relationships among a potentially heterogeneous set of objects is the scientific literature.Results: We first establish a network of related objects by their co-occurrence within MEDLINE records. A set of objects within this network can then be queried to identify shared relationships, and a method is presented to score their statistical relevance by comparing observed frequencies with what would be expected in a random network model. Using Gene Ontology (GO) categories, we demonstrate that this method enables a quantitative ranking of the 'cohesiveness' of a set of objects and, importantly, allows other objects related to this set to be identified and evaluated for their 'cohesion' to it.Supplemental information: A list of ranked genes related to each GO category analyzed can be found at http://innovation.swmed.edu/IRIDESCENT/GO_relationships.htm