C19DM-Neo4j
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)
https://orcid.org/0000-0003-2047-0897
Projects: COVID-19 Disease Map, C19DM-Neo4j
Institutions: Harvard Medical School
https://orcid.org/0000-0001-5709-371X
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
