BBBP

## Dataset Details

### Dataset Description

The blood-brain barrier penetration (BBBP) dataset is designed for the
modeling and prediction of barrier permeability. As a membrane separating
circulating blood and brain extracellular fluid, the blood-brain barrier
blocks most drugs, hormones, and neurotransmitters. Thus penetration of the
barrier forms a long-standing issue in the development of drugs targeting
the central nervous system. This dataset includes binary labels for over 2000
compounds on their permeability properties.

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

### Dataset Sources

- [corresponding publication](https://pubs.acs.org/doi/10.1021/ci300124c)
- [data source](['https://deepchemdata.s3-us-west-1.amazonaws.com/datasets/BBBP.csv'])

## Citation

**BibTeX:**

```bibtex
@article{doi:10.1021/ci300124c,
author = {Martins, Ines Filipa and Teixeira, Ana L. and Pinheiro, Luis and Falcao, Andre O.},
title = {A Bayesian Approach to in Silico Blood-Brain Barrier Penetration Modeling},
journal = {Journal of Chemical Information and Modeling},
volume = {52},
number = {6},
pages = {1686-1697},
year = {2012},
doi = {10.1021/ci300124c},
URL = {https://doi.org/10.1021/ci300124c},
eprint = {https://doi.org/10.1021/ci300124c}}
```

## 数据集详情

### 数据集描述
血脑屏障穿透（blood-brain barrier penetration, BBBP）数据集旨在用于屏障渗透性的建模与预测。血脑屏障作为分隔循环血液与脑细胞外液的膜结构，可阻挡绝大多数药物、激素与神经递质，因此该屏障的穿透性是中枢神经系统靶向药物研发中长期存在的核心问题。本数据集包含超过2000种化合物的渗透性属性二分类标签。

- **整理方：**
- **授权协议：** CC BY 4.0

### 数据集来源
- [相关研究论文](https://pubs.acs.org/doi/10.1021/ci300124c)
- [数据集源文件](https://deepchemdata.s3-us-west-1.amazonaws.com/datasets/BBBP.csv)

## 引用信息

**BibTeX格式：**

bibtex
@article{doi:10.1021/ci300124c,
author = {Martins, Ines Filipa and Teixeira, Ana L. and Pinheiro, Luis and Falcao, Andre O.},
title = {基于贝叶斯方法的硅基（in silico，即计算机模拟）血脑屏障穿透性建模},
journal = {Journal of Chemical Information and Modeling（化学信息与建模杂志）},
volume = {52},
number = {6},
pages = {1686-1697},
year = {2012},
doi = {10.1021/ci300124c},
URL = {https://doi.org/10.1021/ci300124c},
eprint = {https://doi.org/10.1021/ci300124c}}