moses

## Dataset Details

### Dataset Description

Molecular Sets (MOSES) is a benchmark platform
for distribution learning based molecule generation.
Within this benchmark, MOSES provides a cleaned dataset of molecules that are ideal of optimization.
It is processed from the ZINC Clean Leads dataset.

- **Curated by:**
- **License:** CC BY 4.0

### Dataset Sources

- [Article about original dataset](https://arxiv.org/abs/1811.12823)
- [Link to publication of associated dataset - zinc](https://pubs.acs.org/doi/abs/10.1021/acs.jcim.5b00559)
- [Github repository concerning the dataset](https://github.com/molecularsets/moses)

## Citation

**BibTeX:**

```bibtex
@article{10.3389/fphar.2020.565644,
title={{M}olecular {S}ets ({MOSES}): {A} {B}enchmarking {P}latform for {M}olecular {G}eneration {M}odels},
author={Polykovskiy, Daniil and Zhebrak, Alexander and Sanchez-Lengeling, Benjamin and Golovanov,
Sergey and Tatanov, Oktai and Belyaev, Stanislav and Kurbanov, Rauf and Artamonov,
Aleksey and Aladinskiy, Vladimir and Veselov, Mark and Kadurin, Artur and Johansson,
Simon and Chen, Hongming and Nikolenko, Sergey and Aspuru-Guzik, Alan and Zhavoronkov, Alex},
journal={Frontiers in Pharmacology},
year={2020}
}
```

### 数据集详情
#### 数据集概述
分子集（Molecular Sets, MOSES）是一款面向基于分布学习的分子生成任务的基准测试平台。该基准提供了经清洗处理、适配优化任务的理想分子数据集，其原始数据源自ZINC Clean Leads数据集。
- **数据整理方：**
- **授权协议：** CC BY 4.0

### 数据集来源
- [原始数据集相关研究文章](https://arxiv.org/abs/1811.12823)
- [ZINC关联数据集发表论文链接](https://pubs.acs.org/doi/abs/10.1021/acs.jcim.5b00559)
- [本数据集相关GitHub仓库](https://github.com/molecularsets/moses)

## 引用信息
### BibTeX格式引用：
bibtex
@article{10.3389/fphar.2020.565644,
title={{分子集（MOSES）：一款分子生成模型基准测试平台}},
author={Polykovskiy, Daniil and Zhebrak, Alexander and Sanchez-Lengeling, Benjamin and Golovanov,
Sergey and Tatanov, Oktai and Belyaev, Stanislav and Kurbanov, Rauf and Artamonov,
Aleksey and Aladinskiy, Vladimir and Veselov, Mark and Kadurin, Artur and Johansson,
Simon and Chen, Hongming and Nikolenko, Sergey and Aspuru-Guzik, Alan and Zhavoronkov, Alex},
journal={Frontiers in Pharmacology},
year={2020}
}