zpn/lipo
收藏资源简介：
lipo数据集是MoleculeNet的一部分，专注于测量辛醇/水分配系数（logD at pH 7.4）。数据集的注释和语言都是由机器生成的，且数据集是单语的。数据集的大小在1K到10K之间，主要用于生物化学和分子网络领域。数据集的结构包括SMILES和SELFIES分子表示以及目标值logD。数据集被分为训练、验证和测试集，比例为80/10/10，使用骨架分割方法。数据最初由斯坦福的Pande Group生成，并遵循MIT许可发布。
The Lipo dataset is part of MoleculeNet, focusing on measuring the octanol-water partition coefficient (logD at pH 7.4). All annotations and language within the dataset are machine-generated, and the dataset is monolingual. It has a size ranging from 1,000 to 10,000, and is primarily used in the fields of biochemistry and molecular networks. The dataset's structure includes SMILES and SELFIES molecular representations, as well as the target logD values. The dataset is split into training, validation, and test sets at an 80/10/10 ratio using the scaffold splitting method. The data was originally generated by the Pande Group at Stanford University, and is released under the MIT License.
数据集概述
数据集基本信息
- 名称: lipo
- 语言: 单语种（monolingual）
- 许可证: MIT
- 大小: 1K<n<10K
- 标签:
- bio
- bio-chem
- molnet
- molecule-net
- biophysics
- 任务类别: other
数据集描述
数据集摘要
lipo 是 MoleculeNet 中的一个数据集，用于测量辛醇/水分配系数（logD at pH 7.4）的实验结果。
数据集结构
数据字段
数据分割
数据集采用80/10/10的训练/验证/测试分割，使用scaffold split方法。
数据集创建
源数据
数据最初由斯坦福大学的Pande Group生成。
许可证信息
该数据集最初以MIT许可证发布。
引用信息
@misc{https://doi.org/10.48550/arxiv.1703.00564, doi = {10.48550/ARXIV.1703.00564}, url = {https://arxiv.org/abs/1703.00564}, author = {Wu, Zhenqin and Ramsundar, Bharath and Feinberg, Evan N. and Gomes, Joseph and Geniesse, Caleb and Pappu, Aneesh S. and Leswing, Karl and Pande, Vijay}, keywords = {Machine Learning (cs.LG), Chemical Physics (physics.chem-ph), Machine Learning (stat.ML), FOS: Computer and information sciences, FOS: Computer and information sciences, FOS: Physical sciences, FOS: Physical sciences}, title = {MoleculeNet: A Benchmark for Molecular Machine Learning}, publisher = {arXiv}, year = {2017}, copyright = {arXiv.org perpetual, non-exclusive license} }
