Your browser doesn't support javascript.
loading
BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs.
Callaghan, Jackson; Xu, Colleen H; Xin, Jiwen; Cano, Marco Alvarado; Riutta, Anders; Zhou, Eric; Juneja, Rohan; Yao, Yao; Narayan, Madhumita; Hanspers, Kristina; Agrawal, Ayushi; Pico, Alexander R; Wu, Chunlei; Su, Andrew I.
  • Callaghan J; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
  • Xu CH; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
  • Xin J; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
  • Cano MA; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
  • Riutta A; Data Science and Biotechnology, Gladstone Institutes, University of California, San Francisco, CA 94158, United States.
  • Zhou E; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
  • Juneja R; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
  • Yao Y; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
  • Narayan M; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
  • Hanspers K; Data Science and Biotechnology, Gladstone Institutes, University of California, San Francisco, CA 94158, United States.
  • Agrawal A; Data Science and Biotechnology, Gladstone Institutes, University of California, San Francisco, CA 94158, United States.
  • Pico AR; Data Science and Biotechnology, Gladstone Institutes, University of California, San Francisco, CA 94158, United States.
  • Wu C; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
  • Su AI; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
Bioinformatics ; 39(9)2023 Sep 02.
Article en En | MEDLINE | ID: mdl-37707514
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.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Reconocimiento de Normas Patrones Automatizadas Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Reconocimiento de Normas Patrones Automatizadas Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article