Literature Mining for the Discovery of Hidden Connections between Drugs, Genes and Diseases
Literature Mining for the Discovery of Hidden Connections between Drugs, Genes and Diseases
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DOI：
10.1371/journal.pcbi.1000943
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发表时间：
2010-09-01
影响因子：
4.3
通讯作者：
Alkema, Wynand
中科院分区：
文献类型：
--
作者：
Frijters, Raoul;van Vugt, Marianne;Alkema, Wynand
科学文献是检索诸如基因、疾病和细胞过程等生物医学概念之间关联的知识的丰富来源。从文献中建立生物医学概念之间关系的常用方法是共现。除了用于知识检索之外，共现方法也非常适合发现生物医学概念之间新的隐藏关系，遵循简单的abc原则，其中a和C没有直接关系，但通过共享的b中间体连接起来。在本文中，我们描述了CoPub Discovery，这是一个挖掘生物医学概念之间新关系的文献的工具。使用ROC曲线的统计分析表明，CoPub Discovery在广泛的设置和关键字词典中表现良好。随后，我们使用CoPub Discovery来寻找基因、药物、途径和疾病之间的新关系。一些新发现的关系通过独立的文献来源得到了验证。此外，在体外细胞增殖实验中，新的预测化合物与细胞增殖之间的关系得到了验证和证实。结果表明，CoPub Discovery能够识别基因、药物、途径和疾病之间的新关联，这些关联在生物学上很可能是有效的。这使得CoPub Discovery成为一个有用的工具，可以揭示疾病背后的机制，找到新的药物靶点，或者为现有药物找到新的应用。
The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs.