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CoMentG:从科学文献中全面检索生物医学概念之间的通用关系。

CoMentG: comprehensive retrieval of generic relationships between biomedical concepts from the scientific literature.

机构信息

Computational Systems Biology, National Center for Biotechnology (CNB-CSIC), c/ Darwin, 3., Madrid 28049 , Spain.

Department of Molecular Biology and Biochemistry, University of Málaga, Avda. Cervantes, 2., Málaga 29071, Spain.

出版信息

Database (Oxford). 2024 Apr 2;2024. doi: 10.1093/database/baae025.

Abstract

The CoMentG resource contains millions of relationships between terms of biomedical interest obtained from the scientific literature. At the core of the system is a methodology for detecting significant co-mentions of concepts in the entire PubMed corpus. That method was applied to nine sets of terms covering the most important classes of biomedical concepts: diseases, symptoms/clinical signs, molecular functions, biological processes, cellular compartments, anatomic parts, cell types, bacteria and chemical compounds. We obtained more than 7 million relationships between more than 74 000 terms, and many types of relationships were not available in any other resource. As the terms were obtained from widely used resources and ontologies, the relationships are given using the standard identifiers provided by them and hence can be linked to other data. A web interface allows users to browse these associations, searching for relationships for a set of terms of interests provided as input, such as between a disease and their associated symptoms, underlying molecular processes or affected tissues. The results are presented in an interactive interface where the user can explore the reported relationships in different ways and follow links to other resources. Database URL: https://csbg.cnb.csic.es/CoMentG/.

摘要

CoMentG 资源包含了从科学文献中获取的数百万个生物医学感兴趣术语之间的关系。该系统的核心是一种从整个 PubMed 语料库中检测概念的重要共提及的方法。该方法应用于九组术语,涵盖了生物医学概念的最重要类别:疾病、症状/临床体征、分子功能、生物过程、细胞区室、解剖部位、细胞类型、细菌和化合物。我们从广泛使用的资源和本体中获得了超过 74000 个术语之间的 700 多万个关系,其中许多类型的关系在其他资源中都没有。由于术语是从广泛使用的资源和本体中获得的,因此使用它们提供的标准标识符给出了关系,从而可以与其他数据相关联。一个网络界面允许用户浏览这些关联,为提供的一组感兴趣的术语搜索关系,例如疾病与其相关症状、潜在的分子过程或受影响的组织之间的关系。结果以交互界面呈现,用户可以以不同的方式探索报告的关系,并跟随链接到其他资源。数据库网址:https://csbg.cnb.csic.es/CoMentG/。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b0d/10986793/39c9e18a3c4a/baae025f1.jpg

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