Adds Dataset Card for the ProstT5Dataset

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  1. README.md +95 -1
README.md CHANGED
@@ -17,7 +17,101 @@ dataset_info:
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  num_examples: 17070828
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  download_size: 810671738
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  dataset_size: 65394099456
 
 
 
 
 
 
 
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  ---
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  # Dataset Card for "ProstT5Dataset"
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- ## ⚠️ This is work in progress! ⚠️
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  num_examples: 17070828
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  download_size: 810671738
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  dataset_size: 65394099456
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+ license: cc
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+ task_categories:
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+ - text-generation
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+ tags:
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+ - biology
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+ size_categories:
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+ - 10M<n<100M
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  ---
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  # Dataset Card for "ProstT5Dataset"
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+ # Currently under review
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+
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+ * **Contributors:** Michael Heinzinger and Konstantin Weissenow, Joaquin Gomez Sanchez and Adrian Henkel, Martin Steinegger and Burkhard Rost
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+ * **Licence:** TBD
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+
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+ ## Table of Contents
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+ - [Overview](#overview)
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+ - [Dataset Description](#dataset-description)
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+ - [Data Collection and Annotation](#data-collection-and-annotation)
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+ - [Data Splits](#data-splits)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Fields](#data-fields)
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+ - [Data Instances](#data-instances)
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+ - [Data Considerations](#data-considerations)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+ - [Contributions](#contributions)
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+
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+ ## Overview
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+ The ProstT5Dataset is a curated collection of *tokenized* protein sequences and their corresponding structure sequences (3Di).
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+ It is derived from the [AlphaFold Protein Structure Database](https://alphafold.ebi.ac.uk/) and includes various steps of clustering and quality filtering.
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+ To capture 3D information of the sequence, the [3Di structure string representation](https://www.nature.com/articles/s41587-023-01773-0#Sec2) is leveraged. This format
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+ captures the spatial relationship of each residue to its neighbors in 3D space, effectively translating the 3D information of the sequence.
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+ The sequence tokens are generated using the [ProstT5 Tokenizer](https://huggingface.co/Rostlab/ProstT5).
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+
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+ ## Data Fields
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+ - **input_id_x** (3Di Tokens): Corresponding tokenized 3Di structure representation sequences derived from the proteins.
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+ - **input_id_y** (Amino Acid Tokens): Tokenized amino acid sequences of proteins.
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+
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+ ## Dataset Description
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/62c412251f45e8bdb2b05855/BgiKOoFUGjlHDPjbxJWOX.png)
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+ We compare basic protein properties (sequence length, amino acid composition, 3Di-distribution) between our
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+ dataset (training, validation, test sets) and proteins obtained from the [Protein Data Bank (PDB)](https://www.rcsb.org/). Key findings include similar amino acid distributions across datasets,
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+ an overrepresentation of certain 3Di-tokens (d, v, p) and helical structures in AlphaFold2 predictions compared to PDB, and a tendency for shorter protein
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+ lengths in this dataset (average 206-238) relative to PDB proteins (average 255). The analysis also highlights the relationship between
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+ 3Di states and secondary structures, with a notable distinction in strand-related tokens between datasets.
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+
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+ ## Data Collection and Annotation
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+ The dataset began with the AlphaFold Protein Structure Database , undergoing a two-step clustering process and one step of quality filtering:
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+ 1. *First Clustering:* 214M UniprotKB protein sequences were clustered using MMseqs2, resulting in 52M clusters based on pairwise sequence identity.
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+ 2. *Second Clustering:* Foldseek further clustered these proteins into 18.8M clusters, expanded to 18.6M proteins by adding diverse members.
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+ 3. *Quality Filtering:* Removed proteins with low pLDDT scores, short lengths, and highly repetitive 3Di-strings. The final training split contains 17M proteins.
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+
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+ ## Citation
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+ ```
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+ @article{heinzinger2023prostt5,
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+ title={ProstT5: Bilingual language model for protein sequence and structure},
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+ author={Heinzinger, Michael and Weissenow, Konstantin and Sanchez, Joaquin Gomez and Henkel, Adrian and Steinegger, Martin and Rost, Burkhard},
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+ journal={bioRxiv},
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+ pages={2023--07},
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+ year={2023},
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+ publisher={Cold Spring Harbor Laboratory}
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+ }
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+ ```
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+
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+ ## Tokens to Character Mapping
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+ | Amino Acid Representation | 3DI | Special Tokens |
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+ |---------------------------|-----------|--------------------|
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+ | 3: A | 128: a | 0: \<pad\> |
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+ | 4: L | 129: l | 1: \</s\> |
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+ | 5: G | 130: g | 2: \<unk\> |
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+ | 6: V | 131: v | 148: \<fold2AA\> |
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+ | 7: S | 132: s | 149: \<AA2fold\> |
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+ | 8: R | 133: r | |
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+ | 9: E | 134: e | |
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+ | 10: D | 135: d | |
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+ | 11: T | 136: t | |
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+ | 12: I | 137: i | |
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+ | 13: P | 138: p | |
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+ | 14: K | 139: k | |
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+ | 15: F | 140: f | |
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+ | 16: Q | 141: q | |
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+ | 17: N | 142: n | |
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+ | 18: Y | 143: y | |
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+ | 19: M | 144: m | |
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+ | 20: H | 145: h | |
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+ | 21: W | 146: w | |
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+ | 22: C | 147: c | |
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+ | 23: X | | |
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+ | 24: B | | |
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+ | 25: O | | |
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+ | 26: U | | |
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+ | 27: Z | | |
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+