Abstract
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.
Abstract (translated)
我们报告了利用两种目前可用的化学本体来开发用于药物再利用的数据基础设施。数据基础设施包括用分子本体标记增强的化合物 - 目标关联数据库。它还包含两个用于预测新关联的计算工具。我们描述了两种药物再利用系统：一种是基于信息检索策略的用于药物再利用的新生本体信息检索（NOIR-DR），另一种是基于非负矩阵分解和复合相似性的灵感来自推荐者系统。我们报告了这两种工具在药物再利用任务中的表现。
URL
https://arxiv.org/abs/1807.09754
