Normalization of drug and therapeutic concepts with Thera-Py.
Normalization of drug and therapeutic concepts with Thera-Py.
复制标题
用thera-py的药物和治疗概念的归一化。
作者：
命名法和命名策略的多样性使得治疗术语难以管理和协调。随着可用的治疗本体的数量和复杂性不断增加，对协调的跨资源映射的需求变得越来越明显。这项研究创建了协调的概念映射，使链接在一起的相似的概念，尽管依赖于源的数据结构或语义表示的差异。在这项研究中，我们创建了Thera-Py，这是一个Python包和Web API，它使用9个公共资源和词库构建了药物和治疗术语的可搜索概念。通过使用有向图方法，Thera-Py捕获了任何给定治疗药物的常用别名、商品名、注释和关联，并将它们组合在一个概念记录下。我们强调使用Thera-Py从9个不同来源创建了16069个独特的合并治疗概念，并观察到使用Thera-Py协调后，2个或更多知识库中的治疗概念重叠增加（9.8%-41.8%）。我们观察到Thera-Py倾向于将治疗概念规范化为其潜在的活性成分（不包括非药物治疗，例如放射治疗，生物制剂），并统一所有可用的描述符，无论其本体论起源如何。
The diversity of nomenclature and naming strategies makes therapeutic terminology difficult to manage and harmonize. As the number and complexity of available therapeutic ontologies continues to increase, the need for harmonized cross-resource mappings is becoming increasingly apparent. This study creates harmonized concept mappings that enable the linking together of like-concepts despite source-dependent differences in data structure or semantic representation. For this study, we created Thera-Py, a Python package and web API that constructs searchable concepts for drugs and therapeutic terminologies using 9 public resources and thesauri. By using a directed graph approach, Thera-Py captures commonly used aliases, trade names, annotations, and associations for any given therapeutic and combines them under a single concept record. We highlight the creation of 16 069 unique merged therapeutic concepts from 9 distinct sources using Thera-Py and observe an increase in overlap of therapeutic concepts in 2 or more knowledge bases after harmonization using Thera-Py (9.8%-41.8%). We observe that Thera-Py tends to normalize therapeutic concepts to their underlying active ingredients (excluding nondrug therapeutics, eg, radiation therapy, biologics), and unifies all available descriptors regardless of ontological origin.
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影响因子：
2.7
作者：
Quist, Arbor J. L.;Hickman, Thu-Trang T.;Schiff, Gordon D.
通讯作者：
Schiff, Gordon D.
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通讯作者：
Tomasulo, Patricia
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4.5
作者：
Warner, Jeremy L.;Dymshyts, Dmitry;Yang, Peter C.
通讯作者：
Yang, Peter C.
影响因子：
82.9
作者：
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14.9
作者：
Gaulton A;Hersey A;Nowotka M;Bento AP;Chambers J;Mendez D;Mutowo P;Atkinson F;Bellis LJ;Cibrián-Uhalte E;Davies M;Dedman N;Karlsson A;Magariños MP;Overington JP;Papadatos G;Smit I;Leach AR
通讯作者：
Leach AR