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QUERYING PARSE TREE DATABASE OF MEDLINE TEXT TO SYNTHESIZE USER-SPECIFIC BIOMOLECULAR NETWORKS

机译:查询Medline文本的解析树数据库以合成用户特定的生物分子网络

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Curated biological knowledge of interactions and pathways is largely available from various databases, and network synthesis is a popular method to gain insight into the data. However, such data from curated databases presents a single view of the knowledge to the biologists, and it may not be suitable to researchers' specific needs. On the other hand, Medline abstracts are publicly accessible and encode the necessary information to synthesize different kinds of biological networks. In this paper, we propose a new paradigm in synthesizing biomolecular networks by allowing biologists to create their own networks through queries to a specialized database of Medline abstracts. With this approach, users can specify precisely what kind of information they want in the resulting networks. We demonstrate the feasibility of our approach in the synthesis of gene-drug, gene-disease and protein-protein interaction networks. We show that our approach is capable of synthesizing these networks with high precision and even finds relations that have yet to be curated in public databases. In addition, we demonstrate a scenario of recovering a drug-related pathway using our approach.
机译:策划的相互作用和途径的生物学知识在很大程度上可从各种数据库获得,网络合成是一种流行洞察数据的流行方法。然而,来自策划数据库的这种数据呈现给生物学家的知识,并且可能不适合研究人员的特定需求。另一方面,MEDLINE摘要是公开访问的,并编码必要的信息以综合不同类型的生物网络。在本文中,我们通过允许生物学家通过查询来创建自己的网络来合成生物分子网络的新范式。通过这种方法,用户可以确定地指定所得网络中所需的任何类型的信息。我们展示了我们在合成基因 - 药物,基因疾病和蛋白质 - 蛋白质相互作用网络中的方法的可行性。我们表明我们的方法能够以高精度合成这些网络,甚至可以找到尚未在公共数据库中策划的关系。此外,我们展示了使用我们的方法恢复毒品相关途径的情况。

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