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  ---
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  license: cc0-1.0
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  configs:
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- - config_name: default
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  data_files:
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  - split: XL_all
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  path: data/XL_all-*
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  num_examples: 2934
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  download_size: 1448868
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  dataset_size: 14177087
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- pretty_name: PRIDE Crosslinking Archive
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  pretty_name: PRIDE Crosslinking Archive
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: cc0-1.0
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  configs:
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+ - config_name: data
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  data_files:
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  - split: XL_all
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  path: data/XL_all-*
 
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  num_examples: 2934
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  download_size: 1448868
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  dataset_size: 14177087
 
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  pretty_name: PRIDE Crosslinking Archive
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+ ---
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+
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+ # PRIDE Crosslinking Archive
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+ <!-- Provide a quick summary of the dataset. -->
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+ This dataset aggregates publicly available crosslinking mass spectrometry (XL-MS) datasets from the PRIDE repository.
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+ Each dataset is curated and categorized by crosslinking reagent a link type (inter-chain vs intra-chain). For intra-chain links where the protein can be mapped to a
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+ UniProt ID, each link is mapped onto the corresponding AlphaFold Database (AFDB) structure, and the Cα-Cα distance for the linked residue pair is reported.
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+ The result is a standardized resource for analyzing XL-MS constraints across reagents and for benchmarking/evaluating integrative modeling pipelines.
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+ ## Quickstart Usage
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+ ### Install HuggingFace Datasets package
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+ Each subset can be loaded into python using the Huggingface [datasets](https://huggingface.co/docs/datasets/index) library.
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+ First, from the command line install the `datasets` library
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+ $ pip install datasets
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+ Optionally set the cache directory, e.g.
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+ $ HF_HOME=${HOME}/.cache/huggingface/
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+ $ export HF_HOME
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+ then, from within python load the datasets library
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+ >>> import datasets
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+
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+ ### Load model datasets
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+ To load one of the `PRIDE_Crosslinking_Archive` datasets, use `datasets.load_dataset(...)`