TransMiner: mining transitive associations among biological objects from text.
TransMiner: mining transitive associations among biological objects from text.
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TransMiner：从文本中挖掘生物对象之间的传递关联。
DOI：
10.1007/bf02254372
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发表时间：
2004
影响因子：
11
通讯作者：
Potter,DavidA
中科院分区：
文献类型：
--
作者：
Narayanasamy,Vijay;Mukhopadhyay,Snehasis;Palakal,Mathew;Potter,DavidA
基因、蛋白质和药物等生物对象之间的关联可以从科学文献中自动发现。TransMiner是一个通过挖掘科学文献的Medline数据库来寻找对象之间关联的系统。基于同现原理，以关联图的形式发现对象之间的直接关联。传递闭包的原则被应用到关联图中，以找到潜在的传递关联。通过迭代检索和挖掘Medline文档，发现了确实直接的潜在传递关联。在整个Medline数据库中没有明确发现的那些关联是传递性关联，并且是假设生成的候选者。传递性关联根据与两个对象共现的术语的权重之和进行排名。使用图形可视化小程序可视化直接和传递关联。通过在56个乳腺癌基因和钙蛋白酶信号转导通路中的24个对象之间寻找关联来测试TransMiner。TransMiner也被用来重新发现镁和偏头痛之间的联系。
Associations among biological objects such as genes, proteins, and drugs can be discovered automatically from the scientific literature. TransMiner is a system for finding associations among objects by mining the Medline database of the scientific literature. The direct associations among the objects are discovered based on the principle of co-occurrence in the form of an association graph. The principle of transitive closure is applied to the association graph to find potential transitive associations. The potential transitive associations that are indeed direct are discovered by iterative retrieval and mining of the Medline documents. Those associations that are not found explicitly in the entire Medline database are transitive associations and are the candidates for hypothesis generation. The transitive associations were ranked based on the sum of weight of terms that cooccur with both the objects. The direct and transitive associations are visualized using a graph visualization applet. TransMiner was tested by finding associations among 56 breast cancer genes and among 24 objects in the calpain signal transduction pathway. TransMiner was also used to rediscover associations between magnesium and migraine.