---
license: apache-2.0
dataset_info:
  config_name: PDB_Structures
  features:
  - name: name
    dtype: string
  - name: source
    dtype: string
  - name: PDB
    dtype: string
  splits:
  - name: train
    num_bytes: 363960255
    num_examples: 1724
  download_size: 188614040
  dataset_size: 363960255
configs:
- config_name: PDB_Structures
  data_files:
  - split: train
    path: PDB_Structures/data/train-*
---
# FoldDock 
Use AlphaFold2 to predict structures for 65,484 human protein interactions. We show that experiments can orthogonally confirm higher-confidence models. We identify 3,137 high-confidence models, of which 1,371 have no homology to a known structure.>
## Quick Start Usage

### Install Hugging Face Datasets Packages

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 <rmauder/FoldDock> 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")

### <BREIF EXAMPLE OF HOW TO USE DIFFERENT PARTS OF THE DATASET>

## Dataset Details

### Dataset Description <DETAILED DESCRIPTION OF DATASET>

- **Acknowledgements:** <ACKNOWLEDGEMENTS>

- **License:** apache-2.0

### Dataset Sources - **Repository:** https://doi.org/10.17044/scilifelab.16866202.v1 - **Paper:** References
Bryant, P., Pozzati, G., & Elofsson, A. (2021). Data and most relevant results for the FoldDock project [Data set]. doi:10.17044/SCILIFELAB.16866202.V1

## Uses <DESCRIPTION OF INTENDED USE OF DATASET>

### Out-of-Scope Use <DESCRIPTION OF OUT OF SCOPE USES OF DATASET>

### Source Data <DESCRIPTION OF SOURCE DATA>

## Citation 
@misc{https://doi.org/10.17044/scilifelab.16866202.v1,
  doi = {10.17044/SCILIFELAB.16866202.V1},
  url = {https://figshare.scilifelab.se/articles/dataset/Data_and_most_relevant_results_for_the_FoldDock_project/16866202/1},
  author = {Bryant,  Patrick and Pozzati,  Gabriele and Elofsson,  Arne},
  keywords = {Bioinformatics and computational biology not elsewhere classified},
  title = {Data and most relevant results for the FoldDock project},
  publisher = {Stockholm University},
  year = {2021},
  copyright = {Apache 2.0}
}

## Dataset Card Authors