SmartGraph API: Programmatic Knowledge Mining in Network-Pharmacology Setting
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.
Authors
- Ke Will Wang (ORCID: https://orcid.org/0009-0009-8317-8106)
- Michael D. Samuel (ORCID: https://orcid.org/0000-0002-4267-2724)
- Gergely Zahoránszky-Köhalmi (ORCID: https://orcid.org/0000-0002-2534-8770)
- Alexander G. Godfrey (ORCID: https://orcid.org/0000-0003-3386-537X)
- Brandon Walker
- Hythem Sidky (ORCID: https://orcid.org/0000-0003-3532-4809)
- Timothy Sheils (ORCID: https://orcid.org/0000-0002-9987-3738)
- Tudor Ionel Oprea (ORCID: https://orcid.org/0000-0002-6195-6976)
- Jennifer King (ORCID: https://orcid.org/0009-0002-3794-5828)
- Sridhar Vuyyuru
- Jeyaraman Soundarajan
- Nathan Miller (ORCID: https://orcid.org/0000-0002-8934-7857)
- Dhatri V. L. Penna
- Brett Yang
- Jessica Maine
Institutions
- University of New Mexico (US)
- National Center for Advancing Translational Sciences (US)
Publication Details
- Journal
- Journal of Chemical Information and Modeling
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1021/acs.jcim.4c00789
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Center for Advancing Translational Sciences