This article is a Preprint
Preprints are preliminary research reports that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Preprints posted online allow authors to receive rapid feedback and the entire scientific community can appraise the work for themselves and respond appropriately. Those comments are posted alongside the preprints for anyone to read them and serve as a post publication assessment.
A Workflow of Integrated Resources to Catalyze Network Pharmacology Driven COVID-19 Research (preprint)
biorxiv; 2020.
Preprint
in English
| bioRxiv | ID: ppzbmed-10.1101.2020.11.04.369041
ABSTRACT
Motivation In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, host-pathogen and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy. Results:
Here, we describe a workflow we designed for a semi-automated integration of rapidly emerging datasets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 74,805 host-host protein and 1,265 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is accessible via a web interface and via API calls based on the Bolt protocol. We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19.Availability:
https//neo4covid19.ncats.io . Keywords SARS-CoV-2, COVID-19, network pharmacology, graph database, Neo4j, data integration, drug repositioning
Full text:
Available
Collection:
Preprints
Database:
bioRxiv
Main subject:
COVID-19
Language:
English
Year:
2020
Document Type:
Preprint
Similar
MEDLINE
...
LILACS
LIS