OPM

1200 transmembrane and peripheral proteins and peptides from approximately 350 organisms that represent approximately 3800 Protein Data Bank entries. Proteins are classified into classes, superfamilies and families and assigned to 21 distinct membrane types. Spatial positions of proteins with respect to the lipid bilayer are optimized by the PPM 2.0 method that accounts for the hydrophobic, hydrogen bonding and electrostatic interactions of the proteins with the anisotropic water-lipid environment described by the dielectric constant and hydrogen-bonding profiles.

Quickstart Usage

Install HuggingFace Datasets package

Each subset can be loaded into python using the HuggingFace [datasets](https://huggingface.co/docs/datasets/index) library. First, from the command line install the `datasets` library

$ pip install datasets

Optionally set the cache directory, e.g.

$ HF_HOME=${HOME}/.cache/huggingface/
$ export HF_HOME

then, from within python load the datasets library

>>> import datasets

Load model datasets

To load one of the model datasets, use datasets.load\_dataset(...):

>>> dataset_tag = "<DATASET TAG\>"
>>> dataset = datasets.load\_dataset(
  path = "<HF PATH TO DATASET>",
  name = f"{dataset_tag}",
  data_dir = f"{dataset_tag}")['train']

and the dataset is loaded as a datasets.arrow_dataset.Dataset

>>> dataset
<RESULT OF LOADING DATASET MODEL>

which is a column oriented format that can be accessed directly, converted in to a pandas.DataFrame, or parquet format, e.g.

>>> dataset.data.column('<COLUMN NAME IN DATASET>')
>>> dataset.to_pandas()
>>> dataset.to_parquet("dataset.parquet")

Dataset Details

Dataset Description

• Acknowledgements:

• License:

Dataset Sources

• Repository:
• Paper:
• Zenodo Repository:

Uses

Out-of-Scope Use

Source Data

Citation

Dataset Card Authors

<NAME/INFO OF DATASET AUTHORS>