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)

Projects: COVID-19 Disease Map, C19DM-Neo4j
Institutions: Harvard Medical School

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)

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
ROR ID: Not specified
Department: Not specified
Country: United States
City: Harvard
Web page: Not specified
ROR ID: Not specified
Department: Not specified
Country: Luxembourg
City: Luxembourg
Web page: https://wwwde.uni.lu/lcsb
ROR ID: Not specified
Department: Not specified
Country: Japan
City: Not specified
Web page: Not specified