Journal article
Announcing the Biomedical Data Translator: Initial Public Release
Clinical and translational science, v 18(7), e70284
09 Jul 2025
PMID: 40635371
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open-source knowledge graph-based system-Translator-designed to integrate, harmonize, and make inferences over diverse biomedical data sources. We announce here Translator's initial public release and provide an overview of its architecture, standards, user interface, and core features. Translator employs a scalable, federated, knowledge graph framework for the integration of clinical, genomic, pharmacological, and other biomedical knowledge sources, enabling query retrieval, inference, and hypothesis generation. Translator's user interface is designed to support the exploration of knowledge relationships and the generation of insights, without requiring deep technical expertise and gradually revealing more detailed evidence, provenance, and confidence information, as needed by a given user. To demonstrate Translator's application and impact, we highlight features of the user interface in the context of three real-world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism. We discuss strengths and limitations of reasoning within a largely federated system and the need for rich concept modeling and deep provenance tracking. Finally, we outline future directions for enhancing Translator's functionality and expanding its data sources. Translator represents a significant step forward in making complex biomedical knowledge more accessible and actionable, aiming to accelerate translational research and improve patient care.
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Details
- Title
- Announcing the Biomedical Data Translator: Initial Public Release
- Creators
- Karamarie Fecho - University of North Carolina at Chapel HillGwênlyn Glusman - Institute for Systems Biology, Seattle, Washington, USASergio E Baranzini - University of California, San FranciscoChris Bizon - Renaissance Computing InstituteMatthew Brush - University of North Carolina at Chapel HillWilliam Byrd - University of Alabama at BirminghamLawrence Chung - Columbia UniversityAndrew Crouse - University of Alabama at BirminghamEric Deutsch - Institute for Systems BiologyMichel Dumontier - Maastricht UniversityAleksandra Foksinska - University of Alabama at BirminghamJennifer Hadlock - Institute for Systems BiologyKaiwen He - University of Alabama at BirminghamSui Huang - Institute for Systems BiologyRobert Hubal - University of North Carolina at Chapel HillGregory M Hyde - Dartmouth CollegeSharat Israni - University of California, San FranciscoKelyne Kenmogne - University of North Carolina at Chapel HillDavid Koslicki - Pennsylvania State UniversityJana Dorfman Marcette - Montana State University BillingsEwy A Mathe - National Center for Advancing Translational SciencesAbrar Mesbah - CoVar, LLC, Durham, North Carolina, USASierra A T Moxon - Lawrence Berkeley National LaboratoryChristopher J Mungall - Lawrence Berkeley National LaboratoryJohn Osborne - University of Alabama at BirminghamCarrie Pasfield - University of North Carolina at Chapel HillGuangrong Qin - Institute for Systems BiologyStephen A Ramsey - Oregon State UniversityJustin Reese - Lawrence Berkeley National LaboratoryJared C Roach - Institute for Systems BiologyReese Rose - Beshenich Muir & Associates, LLC, Leavenworth, Kansas, USAKarthik Soman - University of California, San FranciscoAndrew I Su - Scripps Research InstituteCasey Ta - Columbia UniversityGaurav Vaidya - Renaissance Computing InstituteRosina Weber - Drexel UniversityQi Wei - Institute for Systems BiologyMark Williams - National Center for Advancing Translational SciencesChunlei Wu - Scripps Research InstituteColleen Xu - Scripps Research InstituteChase Yakaboski - Dartmouth CollegeBiomedical Data Translator Consortium
- Publication Details
- Clinical and translational science, v 18(7), e70284
- Publisher
- Wiley
- Number of pages
- 13
- Grant note
- NCATS
The authors are grateful to members of the Publications Committee at NCATS for their review and approval of the manuscript for submission. Additionally, the authors would like to acknowledge Translator program leadership and the extramural and intramural support provided by NCATS. We note that ChatGPT was used to generate the first draft of Table 1. The authors subsequently refined the content, independent of any artificial intelligence tool.
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Web of Science ID
- WOS:001525017800001
- Scopus ID
- 2-s2.0-105010974964
- Other Identifier
- 991022064829304721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Medicine, Research & Experimental