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arXiv 1807.09754cs.IRcs.AI
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基于本体的药物再利用数据基础设施与方法

Data Infrastructure and Approaches for Ontology-Based Drug Repurposing

IBM Almaden Research Center(IBM阿尔马登研究中心)

Stephen Boyer, Thomas Griffin, Sarath Swaminathan, Kenneth L. Clarkson, Dmitry Zubarev

摘要:

我们报告了一个数据基础设施的发展,利用两个目前可用的化学本体的药物再利用。数据基础设施包括用分子本体标签增强的化合物-靶标关联的数据库。它还包含两个用于预测新关联的计算工具。我们描述了两个药物再利用系统:一个,新生本体信息检索药物再利用(NOIR-DR),基于信息检索策略,另一个,基于非负矩阵分解与化合物相似性,这是受到推荐系统。我们报告了这两种工具在药物再利用任务中的表现。

英文摘要:

We report development of a data infrastructure for drug repurposing that takes advantage of two currently available chemical ontologies. The data infrastructure includes a database of compound- target associations augmented with molecular ontological labels. It also contains two computational tools for prediction of new associations. We describe two drug-repurposing systems: one, Nascent Ontological Information Retrieval for Drug Repurposing (NOIR-DR), based on an information retrieval strategy, and another, based on non-negative matrix factorization together with compound similarity, that was inspired by recommender systems. We report the performance of both tools on a drug-repurposing task.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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