datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MoleculeNet_Tox21
MoleculeNet Tox21
Tox21 dataset [1], part of MoleculeNet [2] benchmark. It is intended to be used through
scikit-fingerprints library.
The task is to predict 12 toxicity targets, including nuclear receptors and stress response pathways. All tasks are binary.
Note that targets have missing values. Algorithms should be evaluated only on present labels. For training data, you may want to impute them, e.g. with zeros.
Characteristic
Description
Tasks
12
Task type
multitask… See the full description on the dataset page: https://huggingface.co/datasets/scikit-fingerprints/MoleculeNet_Tox21.tox21MoleculeNet_Tox21
Mirrored by Aurigene AI
Discovery stage: Lead optimization
Nuclear-receptor and stress-response toxicity assays from the Tox21 challenge. Multi-task classification.
Rows: 7,831 (tox21.csv 7,831)
Pairs with Aurigene-AI/ChemBERTa-77M-MTR from our model catalogue.
Upstream: scikit-fingerprints/MoleculeNet_Tox21 - all credit to the original authors and to the researchers who produced the underlying data; the dataset card and licence below are theirs.
Explore the rest of the… See the full description on the dataset page: https://huggingface.co/datasets/Aurigene-AI/MoleculeNet_Tox21.TOX21tox21tox21_SRp53
Dataset Summary
tox21_SRp53 is a dataset included in MoleculeNet. The "Toxicology in the 21st Century" (Tox21) initiative created a public database measuring toxicity of compounds, which has been used in the 2014 Tox21 Data Challenge. This dataset contains qualitative toxicity measurements for 8k compounds on 12 different targets, including nuclear receptors and stress response pathways.
Dataset Structure
Data Fields
Each split contains
smiles: the… See the full description on the dataset page: https://huggingface.co/datasets/SauravMaheshkar/tox21_SRp53.tox21tox21tox21