Update README.md

README.md

@@ -41,6 +41,7 @@ In order to be able to do relevant analysis with the embeddings, the correspondi
   * **GO annotations**: this column contains a semicolon-separated string of GO annotations associated with that sequence.
 * **Raw metadata** (*Original_Metadata.tsv.gz*): in *.tsv* format, this file contains extended metadata directly obtained from Swiss-Prot/Uniprot.
 * **Source script** (*ESM2_script.py*): in *.py* format, this script generated the embeddings directly from the source data.
+* **Classification analysis** (*ESM2_Classification.ipynb*): Jupyter Notebook that parses the embeddings and the metadata in order to perform a classification task on the 20 most common GO annotations for the Human sequences. A Random Forest classifier or a LightGBM classifier is fitted for every annotation and a prediction is made on a test split, obtaining relevant metrics. It also contains PCA and UMAP analysis of the embeddings.
 
 ## What is the purpose of this dataset?