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KG-COVID-19: a framework to produce customized knowledge graphs for COVID-19 response
2020
Patterns
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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. ...
KG-COVID-19 is a framework for producing knowledge graphs that can be customized for downstream applications including machine learning tasks, hypothesis-based querying, and browsable user interface to ...
doi:10.1016/j.patter.2020.100155
pmid:33196056
pmcid:PMC7649624
fatcat:bkoqhgb7mjf7roajxw4ohxuvgu
KG-COVID-19: a framework to produce customized knowledge graphs for COVID-19 response
[article]
2020
biorxiv/medrxiv
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
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To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates biomedical data to produce knowledge graphs (KGs) for COVID-19 response. ...
Integrated, up-to-date data about SARS-CoV-2 and coronavirus disease 2019 (COVID-19) is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. ...
KG-COVID-19 is a framework for producing knowledge graphs that can be customized for downstream applications including machine learning tasks, hypothesis-based querying, and browsable user interface to ...
doi:10.1101/2020.08.17.254839
pmid:32839776
pmcid:PMC7444288
fatcat:kiiqbvcigfcchm4v6ikoz5umju
KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response
2020
Social Science Research Network
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
as: Reese et al., KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response, Patterns (2020), https://doi.org/10.1016/j.patter.2020.100155 ...
Reese et al., KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response, Patterns (2020), https://doi.org/10.1016/j.patter.2020.100155
Please cite this article in press ...
doi:10.2139/ssrn.3681978
fatcat:pkm3aschdfajtg4v6mqzy47ofm
The National COVID Cohort Collaborative (N3C): Rationale, Design, Infrastructure, and Deployment
2020
Zenodo
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data for COVID-19 analytics. ...
Objective COVID-19 poses societal challenges that require expeditious data and knowledge sharing. ...
ACKNOWLEDGEMENTS STATEMENT We acknowledge the Oregon Clinical and Translational Research Institute for their guidance and review of N3C plans and regulatory processes as they unfolded. ...
doi:10.5281/zenodo.3979622
fatcat:ocgmyerqtvfdhnw23r3jjy7r6i
The National COVID Cohort Collaborative (N3C): Rationale, Design, Infrastructure, and Deployment
2020
JAMIA Journal of the American Medical Informatics Association
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The file type is application/pdf.
data for COVID-19 analytics. ...
Objective COVID-19 poses societal challenges that require expeditious data and knowledge sharing. ...
and a variety of KGs covering a range of biological entities such as genes, biological processes, and diseases; the KG-COVID-19 98 knowledge graph also includes literature annotation. ...
doi:10.1093/jamia/ocaa196
pmid:32805036
pmcid:PMC7454687
fatcat:rgaafgl6k5hjvlbpphcdcdr6ie
A critical overview of computational approaches employed for COVID-19 drug discovery
2021
Chemical Society Reviews
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We cover diverse methodologies, computational approaches, and case studies illustrating the ongoing efforts to develop viable drug candidates for treatment of COVID-19. ...
AWS has also generated a similar biological knowledge graph, called DRKG, to fight COVID-19. ...
The use of knowledge graph approaches for COVID-19 drug repurposing Biomedical Knowledge Graphs (KG) aim to provide a high level overview of the association between diseases (symptoms, ontologies, etc. ...
doi:10.1039/d0cs01065k
pmid:34212944
pmcid:PMC8371861
fatcat:n6dxyyjxifh6hoehd7myapjtwu
Learning deep translational patient representations: systematic integration of clinical records and biomedical knowledge
[article]
2022
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These experiments were used to develop a joint learning framework for inferring molecular characterizations of patients from clinical data. ...
Finally, an algorithm that losslessly transforms complex knowledge graphs (KGs) into representations more suitable for inductive inference was developed and validated through the generation of expert-verified ...
With respect to Availability and Usability, PheKnowLator and six other methods (i.e., the Clinical Knowledge Graph, Hetionet, KaBOB, kg-covid-19, KGTK, and Knowledge Graph Exchange) performed equally well ...
doi:10.25677/se22-we57
fatcat:sjoxgbfatvdvha7w6kgi2izape