---
tags:
- chemistry
- smiles
- molecules
- cheminformatics
- classification
pretty_name: COVID-19 Classification
size_categories:
- 1K<n<10K
---

# COVID-19 Classification

Binary classification dataset of small molecules represented as SMILES for predicting anti‑coronavirus (SARS‑CoV‑2) activity.

## Source
- [Original dataset CSV](https://github.com/Harigua/ML_DD-applications/blob/main/COVID-19/data.csv)

## Data fields
- `smiles` (string): Canonical, isomeric SMILES. Unmodified from the source.
- `label` (int): Binary activity label, {0: Inactive, 1: Active}.

## Citation
Harigua-Souiai, E.; Heinhane, M.M.; Abdelkrim, Y.Z.; Souiai, O.; Abdeljaoued-Tej, I.; Guizani, I. Deep Learning Algorithms Achieved Satisfactory Predictions When Trained on a Novel Collection of Anticoronavirus Molecules. Frontiers in Genetics, 2021, 12:744170. https://doi.org/10.3389/fgene.2021.744170

Please cite the authors above if you use this dataset.