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Rapid interaction profiling of 2019-nCoV for network-based deep drug-repurpose learning (DDRL)

Project description

Applying deep learning to investigate the coronavirus–host interaction

The COVID-19 pandemic has taught us that it is necessary to understand the virus's interaction with the host in order to design effective therapeutics. The EU-funded RiPCoN project will analyse protein–protein interactions and protein–RNA interaction predictions between virus and host and feed this information into an existing deep learning model. This will generate a public resource for translational and basic coronavirus research and help identify approved drugs that are likely effective against 2019-nCoV. Most importantly, scientists will examine how genetic variations in both humans and the virus are jointly responsible for disease severity, hoping to improve risk management and preparedness for future outbreaks.

Coordinator

HELMHOLTZ ZENTRUM MUENCHEN DEUTSCHES FORSCHUNGSZENTRUM FUER GESUNDHEIT UND UMWELT GMBH
Net EU contribution
€ 800 635,00
Address
Ingolstadter Landstrasse 1
85764 Neuherberg
Germany

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Region
Bayern Oberbayern München, Landkreis
Activity type
Research Organisations
Non-EU contribution
€ 0,00

Participants (2)

INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE
France
Net EU contribution
€ 232 500,00
Address
Rue De Tolbiac 101
75654 Paris

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Region
Ile-de-France Ile-de-France Paris
Activity type
Research Organisations
Non-EU contribution
€ 0,00
FUNDACIO INSTITUT DE RECERCA BIOMEDICA (IRB BARCELONA)
Spain
Net EU contribution
€ 197 500,00
Address
Carrer Baldiri Reixac 10-12 Parc Scientific De Barcelona
08028 Barcelona

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Region
Este Cataluña Barcelona
Activity type
Research Organisations
Non-EU contribution
€ 0,00