blood_brain_barrier_martins_et_al

## Dataset Details

### Dataset Description

As a membrane separating circulating blood and brain extracellular
fluid, the blood-brain barrier (BBB) is the protection layer that blocks most
foreign drugs. Thus the ability of a drug to penetrate the barrier to deliver
to the site of action forms a crucial challenge in development of drugs for the
central nervous system.

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

### Dataset Sources

- [corresponding publication](https://doi.org/10.1021/ci300124c)
- [corresponding publication](https://rb.gy/0xx91v)
- [data source](https://tdcommons.ai/single_pred_tasks/adme/#bbb-blood-brain-barrier-martins-et-al)

## Citation

**BibTeX:**

```bibtex
@article{Martins2012,
doi = {10.1021/ci300124c},
url = {https://doi.org/10.1021/ci300124c},
year = {2012},
month = jun,
publisher = {American Chemical Society (ACS)},
volume = {52},
number = {6},
pages = {1686--1697},
author = {Ines Filipa Martins and Ana L. Teixeira and Luis Pinheiro
and Andre O. Falcao},
title = {A Bayesian Approach to in Silico Blood-Brain Barrier Penetration Modeling},
journal = {Journal of Chemical Information and Modeling}
@article{Wu2018,
doi = {10.1039/c7sc02664a},
url = {https://doi.org/10.1039/c7sc02664a},
year = {2018},
publisher = {Royal Society of Chemistry (RSC)},
volume = {9},
number = {2},
pages = {513--530},
author = {Zhenqin Wu and Bharath Ramsundar and Evan~N. Feinberg and Joseph
Gomes and Caleb Geniesse and Aneesh S. Pappu and Karl Leswing and Vijay Pande},
title = {MoleculeNet: a benchmark for molecular machine learning},
journal = {Chemical Science}
```

## 数据集详情
### 数据集描述
血脑屏障（blood-brain barrier, BBB）是分隔循环血液与脑组织细胞外液的生物膜，亦是阻挡绝大多数外源性药物的保护性屏障。因此，药物穿透该屏障并抵达作用靶点的能力，是中枢神经系统（central nervous system, CNS）药物研发过程中的核心挑战之一。
- **数据整理方：**
- **许可协议：** CC BY 4.0

### 数据集来源
- [相关研究论文](https://doi.org/10.1021/ci300124c)
- [相关研究论文](https://rb.gy/0xx91v)
- [数据源](https://tdcommons.ai/single_pred_tasks/adme/#bbb-blood-brain-barrier-martins-et-al)

## 引用
**BibTeX格式引用：**
bibtex
@article{Martins2012,
doi = {10.1021/ci300124c},
url = {https://doi.org/10.1021/ci300124c},
year = {2012},
month = jun,
publisher = {美国化学会（ACS）},
volume = {52},
number = {6},
pages = {1686--1697},
author = {Ines Filipa Martins and Ana L. Teixeira and Luis Pinheiro and Andre O. Falcao},
title = {贝叶斯方法用于计算机（in silico）血脑屏障穿透建模},
journal = {Journal of Chemical Information and Modeling}
@article{Wu2018,
doi = {10.1039/c7sc02664a},
url = {https://doi.org/10.1039/c7sc02664a},
year = {2018},
publisher = {英国皇家化学会（RSC）},
volume = {9},
number = {2},
pages = {513--530},
author = {Zhenqin Wu and Bharath Ramsundar and Evan~N. Feinberg and Joseph Gomes and Caleb Geniesse and Aneesh S. Pappu and Karl Leswing and Vijay Pande},
title = {MoleculeNet：分子机器学习基准数据集},
journal = {Chemical Science}

搜集汇总

背景与挑战

背景概述

该数据集关注血脑屏障（BBB），它作为保护层分隔血液和大脑细胞外液，阻碍药物进入，因此药物穿透该屏障的能力是中枢神经系统药物开发的重要挑战。数据集基于相关研究，用于支持药物渗透性建模。