The recent SmartGraph platform facilitates the execution of complex drug-discovery workflows with ease in the network-pharmacology paradigm. However, at the time of its publication we identified the need for the development of an Application Programming Interface (API) that could promote biomedical data integration and hypothesis generation in an automated manner. This need was magnified at the time of the COVID-19 pandemic. This study addresses the absence of such an API. Accordingly, most functionalities of the original platform were implemented within the SmartGraph API. We demonstrate that by using the API it is possible to transform the original semiautomated workflow behind the Neo4COVID19 database to a fully automated one. The availability of the SmartGraph API lends a significant improvement to the programmatic integration of network-pharmacology-oriented knowledge graphs and analytics, as well as predictive functionalities and workflows.
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http://dx.doi.org/10.1021/acs.jcim.4c00789 | DOI Listing |
J Chem Inf Model
December 2024
Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, New Mexico 87131, United States.
The recent SmartGraph platform facilitates the execution of complex drug-discovery workflows with ease in the network-pharmacology paradigm. However, at the time of its publication we identified the need for the development of an Application Programming Interface (API) that could promote biomedical data integration and hypothesis generation in an automated manner. This need was magnified at the time of the COVID-19 pandemic.
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