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Using standard systems biology methodologies a 14-compartment dynamic model was developed for the Corona virus epidemic. The model predicts that: (i) it will be impossible to limit lockdown intensity such that sufficient herd immunity develops for this epidemic to die down, (ii) the death toll from the SARS-CoV-2 virus decreases very strongly with increasing intensity of the lockdown, but (iii) the duration of the epidemic increases at first with that intensity and then decreases again, such that ...
Programme: Model repository for M4 (Make Me My Model) clients of ISBE
Public web page: Not specified
Start date: 1st Mar 2020
End date: 24th Mar 2023
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
Here we share resources and best practices to develop a disease map for COVID-19. The project is progressing as a broad community-driven effort. We aim to establish a knowledge repository on virus-host interaction mechanisms specific to the SARS-CoV-2. The COVID-19 Disease Map is an assembly of molecular interaction diagrams established based on literature evidence.
Programme: Disease Maps
Public web page: http://doi.org/10.17881/covid19-disease-map
Programme: Independent Projects
Public web page: Not specified