BioThings Explorer:用于生物医学API的联合知识图的查询引擎。

IF 4.4 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Bioinformatics Pub Date : 2023-09-02 DOI:10.1093/bioinformatics/btad570
Jackson Callaghan, Colleen H Xu, Jiwen Xin, Marco Alvarado Cano, Anders Riutta, Eric Zhou, Rohan Juneja, Yao Yao, Madhumita Narayan, Kristina Hanspers, Ayushi Agrawal, Alexander R Pico, Chunlei Wu, Andrew I Su
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引用次数: 0

摘要

摘要:知识图是一种越来越常见的用于表示生物医学信息的数据结构。这些知识图可以很容易地表示异构类型的信息,并且存在许多用于查询和分析图的算法和工具。生物医学知识图谱已被用于多种应用,包括药物再利用、药物靶点识别、药物副作用预测和临床决策支持。通常,知识图是通过集中和集成来自多个不同来源的数据来构建的。在这里,我们描述了BioThings Explorer,它是一个应用程序,可以查询从生物医学web服务网络中的聚合信息派生的虚拟联合知识图。BioThings Explorer利用每个资源的输入和输出的语义精确注释,并自动链接web服务调用以执行多步骤图查询。因为没有大型的、集中的知识图需要维护,所以BioThings Explorer是作为一个轻量级应用程序分发的,它在查询时动态检索信息。可用性和实施:更多信息可在https://explorer.biothings.io代码可在https://github.com/biothings/biothings_explorer.
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BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs.

Summary: Knowledge graphs are an increasingly common data structure for representing biomedical information. These knowledge graphs can easily represent heterogeneous types of information, and many algorithms and tools exist for querying and analyzing graphs. Biomedical knowledge graphs have been used in a variety of applications, including drug repurposing, identification of drug targets, prediction of drug side effects, and clinical decision support. Typically, knowledge graphs are constructed by centralization and integration of data from multiple disparate sources. Here, we describe BioThings Explorer, an application that can query a virtual, federated knowledge graph derived from the aggregated information in a network of biomedical web services. BioThings Explorer leverages semantically precise annotations of the inputs and outputs for each resource, and automates the chaining of web service calls to execute multi-step graph queries. Because there is no large, centralized knowledge graph to maintain, BioThings Explorer is distributed as a lightweight application that dynamically retrieves information at query time.

Availability and implementation: More information can be found at https://explorer.biothings.io and code is available at https://github.com/biothings/biothings_explorer.

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来源期刊
Bioinformatics
Bioinformatics 生物-生化研究方法
CiteScore
11.20
自引率
5.20%
发文量
753
审稿时长
2.1 months
期刊介绍: The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.
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