update readme

README.md

@@ -1,3 +1,47 @@
----
-license: mit
----
+---
+license: mit
+language:
+- en
+---
+This dataset provides the predicted three-dimensional structures corresponding to the Tasks Assessing Protein Embeddings (TAPE) benchmark. Specifically, it encompasses the structural data generated for the stability, fluorescence, and protein-protein interaction (PPI) affinity tasks.
+
+The reference for the TAPE benchmark is:
+
+```bibtex
+@inproceedings{tape2019,
+author = {Rao, Roshan and Bhattacharya, Nicholas and Thomas, Neil and Duan, Yan and Chen, Xi and Canny, John and Abbeel, Pieter and Song, Yun S},
+title = {Evaluating Protein Transfer Learning with TAPE},
+booktitle = {Advances in Neural Information Processing Systems}
+year = {2019}
+}
+
+@article{sarkisyan2016,
+  title={Local fitness landscape of the green fluorescent protein},
+  author={Sarkisyan, Karen S and Bolotin, Dmitry A and Meer, Margarita V and Usmanova, Dinara R and Mishin, Alexander S and Sharonov, George V and Ivankov, Dmitry N and Bozhanova, Nina G and Baranov, Mikhail S and Soylemez, Onuralp and others},
+  journal={Nature},
+  volume={533},
+  number={7603},
+  pages={397},
+  year={2016},
+  publisher={Nature Publishing Group}
+}
+
+@article{proteinnet,
+  title={ProteinNet: a standardized data set for machine learning of protein structure},
+  author={AlQuraishi, Mohammed},
+  journal={arXiv preprint arXiv:1902.00249},
+  year={2019}
+}
+
+@article{rocklin2017,
+  title={Global analysis of protein folding using massively parallel design, synthesis, and testing},
+  author={Rocklin, Gabriel J and Chidyausiku, Tamuka M and Goreshnik, Inna and Ford, Alex and Houliston, Scott and Lemak, Alexander and Carter, Lauren and Ravichandran, Rashmi and Mulligan, Vikram K and Chevalier, Aaron and others},
+  journal={Science},
+  volume={357},
+  number={6347},
+  pages={168--175},
+  year={2017},
+  publisher={American Association for the Advancement of Science}
+}
+
+```