We used the Neo4j graph database approach to integrate the content of the COVID-19 Disease Map diagrams to efficiently access, query and manage the content of these diagrams and enable communication with external resources, such as Reactome and Recon, that already provide support via a similar environment.
Web page: Not specified
Funding details:Related items
Postdoctoral researcher at Luxembourg Centre For Systems Biomedicine (LCSB), University of Luxembourg
Projects: C19DM-Neo4j
Institutions: Luxembourg Centre for Systems Biomedicine (LCSB)
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Projects: COVID-19 Disease Map, C19DM-Neo4j
Institutions: Harvard Medical School
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Expertise: Curation, Data Integration
Projects: HUMET Startup, COVID-19 Disease Map, C19DM-Neo4j
Institutions: European Institute for Systems Biology and Medicine, Luxembourg Centre for Systems Biomedicine (LCSB)
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Expertise: Systems Biology, Systems Medicine, Disease Maps, Systems Biology Graphical Notation
Tools: SBGN, CellDesigner, SBGN-ED, Newt Editor
We used the Neo4j graph database approach to integrate the content of the COVID-19 Disease Map diagrams to efficiently access, query and manage the content of these diagrams and enable communication with external resources, such as Reactome and Recon, that already provide support via a similar environment. This work complements the efforts on exploring COVID-19 disease mechanisms within the COVID-19 Disease Map Project.
Programme: C19DM-Neo4j
Public web page: Not specified
Start date: 1st Sep 2020
End date: 31st Dec 2022