Update README.md

README.md

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 # ESM2 Protein Function Caller
 
-An Evolutionary-scale Model (ESM) for protein function calling from amino acid sequences. Based on the ESM2 architecture and fine-tuned on the [CAFA 5](https://huggingface.co/datasets/andrewdalpino/CAFA5) dataset, this model predicts the gene ontology (GO) subgraph for a particular protein sequence - giving you insight into the molecular function, biological process, and location of the activity inside the cell.
+An Evolutionary-scale Model (ESM) for protein function calling from amino acid sequences. Based on the ESM2 Transformer architecture and fine-tuned on the [CAFA 5](https://huggingface.co/datasets/andrewdalpino/CAFA5) dataset, this model predicts the gene ontology (GO) subgraph for a particular protein sequence - giving you insight into the molecular function, biological process, and location of the activity inside the cell.
 
 **Note**: This model specilizes on the `celluar component` subgraph of the gene ontology.
 
@@ -84,4 +84,12 @@ print(f"{probability:.4f}: {term}")
 - **Epochs**: 20
 - **Test F1**: 0.63
 - **Test Precision**: 0.78
-- **Test Recall**: 0.53
+- **Test Recall**: 0.53
+
+## References:
+
+>- A. Rives, et al. Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences, 2021.
+>- Z. Lin, et al. Evolutionary-scale prediction of atomic level protein structure with a language model, 2022.
+>- G. A. Merino, et al. Hierarchical deep learning for predicting GO annotations by integrating protein knowledge, 2022.
+>- I. Friedberg, et al. CAFA 5 Protein Function Prediction. https://kaggle.com/competitions/cafa-5-protein-function-prediction, 2023.
+>- M. Ashburner, et al. Gene Ontology: tool for the unification of biology, 2000.