load_cyp3a4_veith#
- skfp.datasets.tdc.adme.load_cyp3a4_veith(data_dir: str | PathLike | None = None, as_frame: bool = False, verbose: bool = False) DataFrame | tuple[list[str]] | ndarray#
Load the CYP3A4 subset of CYP P450 Veith dataset.
The CYP P450 genes are involved in the formation and breakdown (metabolism) of various molecules and chemicals within cells. The task is to predict CYP3A4 inhibition. CYP3A4 is an important enzyme in the body, mainly found in the liver and in the intestine. It oxidizes small foreign organic molecules (xenobiotics), such as toxins or drugs, so that they can be removed from the body [1] [2].
All CYP P450 Veith subsets:
This dataset is a part of “metabolism” subset of ADME tasks.
Tasks
1
Task type
classification
Total samples
12328
Recommended split
scaffold
Recommended metric
AUPRC
- Parameters:
data_dir ({None, str, path-like}, default=None) – Path to the root data directory. If
None, currently set scikit-learn directory is used, by default $HOME/scikit_learn_data.as_frame (bool, default=False) – If True, returns the raw DataFrame with columns: “SMILES”, “label”. Otherwise, returns SMILES as list of strings, and labels as a NumPy array (1D integer binary vector).
verbose (bool, default=False) – If True, progress bar will be shown for downloading or loading files.
- Returns:
data – Depending on the
as_frameargument, one of: - Pandas DataFrame with columns: “SMILES”, “label” - tuple of: list of strings (SMILES), NumPy array (labels)- Return type:
pd.DataFrame or tuple(list[str], np.ndarray)
References