Adds Dataset Card for the ProstT5Dataset (#2)

- Adds Dataset Card for the ProstT5Dataset (522317c1e4afb6cd9cb1c9dd0fa05fc5664613e2)


Co-authored-by: Adrian Henkel <[email protected]>

README.md

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