ArticlePatterns (New York, N.Y.)2021
KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response.
Article in Patterns (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
44 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Graph databases in systems biology: a systematic review.Briefings in bioinformatics · 2024Pooled it
- MetagenomicKG: a knowledge graph for metagenomic applications.Bioinformatics (Oxford, England) · 2026Article
- Therapeutic monoclonal antibodies repurposing in oncology via IMGT/mAb-KG embeddings.BMC medical informatics and decision making · 2026Article
- Leveraging knowledge graphs and large language models for integrating molecular variants and clinical insights in COVID-19 research.Biosafety and health · 2026Article
- Natural language processing-driven knowledge graphs for transformative public health intelligence and research datasets in urgent and emergency care.Frontiers in public health · 2026Article
- VaxKG: Integrating The Vaccine Ontology And VIOLIN For Advanced Vaccine Queries And LLM-Powered Chat Systems.bioRxiv : the preprint server for biology · 2025Article
- medicX-KG: a knowledge graph for pharmacists' drug information needs.Journal of biomedical semantics · 2025Article
- Federated SPARQL query performance evaluation for exploring disease model mouse: combining gene expression, orthology, and disease knowledge graphs.BMC medical informatics and decision making · 2025Article
- Hypothesizing mechanistic links between microbes and disease using knowledge graphs.Scientific reports · 2025Article
- A change language for ontologies and knowledge graphs.Database : the journal of biological databases and curation · 2025Article
- Petagraph: A large-scale unifying knowledge graph framework for integrating biomolecular and biomedical data.Scientific data · 2024Article
- KnowVID-19: A Knowledge-Based System to Extract Targeted COVID-19 Information from Online Medical Repositories.Biomolecules · 2024Article
- An open source knowledge graph ecosystem for the life sciences.Scientific data · 2024Article
- MetagenomicKG: a knowledge graph for metagenomic applications.bioRxiv : the preprint server for biology · 2024Article
- Informatic challenges and advances in illuminating the druggable proteome.Drug discovery today · 2024Review
- VaxKG: Integrating The Vaccine Ontology And VIOLIN For Advanced Vaccine Queries And LLM-Powered Chat Systems.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- A scalable tool for analyzing genomic variants of humans using knowledge graphs and graph machine learning.Frontiers in big data · 2024Article
- The importance of graph databases and graph learning for clinical applications.Database : the journal of biological databases and curation · 2023Review
- KG-Hub-building and exchanging biological knowledge graphs.Bioinformatics (Oxford, England) · 2023Article
- Lessons learned to enable question answering on knowledge graphs extracted from scientific publications: A case study on the coronavirus literature.Journal of biomedical informatics · 2023Article
Corrections and comments
- Update of
Authors and funding
18 authors.
Funding
Abstract
Integrated, up-to-date data about SARS-CoV-2 and COVID-19 is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time-consuming, since much of it is in siloed databases or in textual format. Furthermore, the data required by the research community vary drastically for different tasks; the optimal data for a machine learning task, for example, is much different from the data used to populate a browsable user interface for clinicians. To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates heterogeneous biomedical data to produce knowledge graphs (KGs), and applied it to create a KG for COVID-19 response. This KG framework also can be applied to other problems in which siloed biomedical data must be quickly integrated for different research applications, including future pandemics.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.