# Heterogeneous network-based drug repurposing for COVID-19

arXiv: https://arxiv.org/abs/2107.09217 · HTML: https://mlsanity.com/paper/2107.09217/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 7 references that are in the map.
- First posted on arXiv 20 Jul 2021.

## Builds on (most cited first, 2 of 2)

- [Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19](https://mlsanity.com/paper/2004.07229/) (2020)
- [PU Learning for Matrix Completion](https://mlsanity.com/paper/1411.6081/) (2014)

## Abstract (arXiv)

The Corona Virus Disease 2019 (COVID-19) belongs to human coronaviruses (HCoVs), which spreads rapidly around the world. Compared with new drug development, drug repurposing may be the best shortcut for treating COVID-19. Therefore, we constructed a comprehensive heterogeneous network based on the HCoVs-related target proteins and use the previously proposed deepDTnet, to discover potential drug candidates for COVID-19. We obtain high performance in predicting the possible drugs effective for COVID-19 related proteins. In summary, this work utilizes a powerful heterogeneous network-based deep learning method, which may be beneficial to quickly identify candidate repurposable drugs toward future clinical trials for COVID-19. The code and data are available at https://github.com/stjin-XMU/HnDR-COVID.