Update README.md

README.md

@@ -21,4 +21,73 @@ configs:
     path: data/train-*
   - split: test
     path: data/test-*
+task_categories:
+- text-classification
+tags:
+- chemistry
+- biology
+size_categories:
+- 10K<n<100K
 ---
+
+
+# Dataset Card for TCR_pMHC_Affinity Dataset
+
+### Dataset Summary
+
+The interaction between T cell receptors (TCRs) and peptide-major histocompatibility complexes (pMHCs) plays a crucial role in the recognition and activation of T cells in the immune system. TCRs are cell surface receptors found on T cells, and pMHCs are complexes formed by peptides derived from antigens bound to major histocompatibility complexes (MHCs) on the surface of antigen-presenting cells. The classification task is to predict whether a given paired TCR sequence and peptide can bind or not. 
+
+## Dataset Structure
+
+### Data Instances
+For each instance, there is a string representing the protein sequence and an integer label indicating whether a given paired TCR sequence and peptide can bind or not. See the [TCR_pMHC_Affinity dataset viewer](https://huggingface.co/datasets/Bo1015/tcr_pmhc_affinity/viewer) to explore more examples.
+
+```
+{'seq':'CAGADGGSQGNLIF|CASSTRSTDTQYF|GILGFVFTL'
+'label':1}
+```
+
+The average  for the `seq` and the `label` are provided below:
+
+| Feature    | Mean Count |
+| ---------- | ---------------- |
+| seq    | 39    |
+| label (0)    | 0.83    |
+| label (1)   | 0.17    |
+
+
+### Data Fields
+
+- `seq`: a string containing the protein sequence
+- `label`: an integer label indicating whether a given paired TCR sequence and peptide can bind or not.
+
+### Data Splits
+
+The  TCR_pMHC_Affinity dataset has 2 splits: _train_ and _test_. Below are the statistics of the dataset.
+
+| Dataset Split | Number of Instances in Split                |
+| ------------- | ------------------------------------------- |
+| Train         | 19,526                            |
+| Test          | 4,485                                      |
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+ The dataset is major from [VDJdb](https://vdjdb.cdr3.net/), processed and curated from [epiTCR](https://academic.oup.com/bioinformatics/article/39/5/btad284/7140137).
+
+
+### Citation
+If you find our work useful, please consider citing the following paper:
+
+```
+@misc{chen2024xtrimopglm,
+  title={xTrimoPGLM: unified 100B-scale pre-trained transformer for deciphering the language of protein},
+  author={Chen, Bo and Cheng, Xingyi and Li, Pan and Geng, Yangli-ao and Gong, Jing and Li, Shen and Bei, Zhilei and Tan, Xu and Wang, Boyan and Zeng, Xin and others},
+  year={2024},
+  eprint={2401.06199},
+  archivePrefix={arXiv},
+  primaryClass={cs.CL},
+  note={arXiv preprint arXiv:2401.06199}
+}
+```