Update README.md

README.md

@@ -11,7 +11,9 @@ size_categories:
 dataset_summary: >-
   AggregatorAdvisor identifies molecules that are known to aggregate or may aggregate in biochemical assays.
   The approach is based on the chemical similarity to known aggregators, and physical properties.
-  The AggregatorAdvisor dataset contains 12645 compounds from 20 different sources.
+  
+  The train and test datasets uploaded to our Hugging Face repository have been sanitized and split from the original dataset, which contains 12645 compounds.
+  If you want to try these processes with the original dataset, please follow the instructions in the Processing Script.py[https://huggingface.co/datasets/maomlab/AggregatorAdvisor/blob/main/Preprocessing%20Script.py] file located in the AggregatorAdvisor.
 citation: >-
   @article 
     {Irwin2015, title = {An Aggregation Advisor for Ligand Discovery},
@@ -73,7 +75,7 @@ then, from within python load the datasets library
 
     >>> import datasets
    
-and load one of the `HematoxLong2023` datasets, e.g.,
+and load one of the `AggregatorAdvisor` datasets, e.g.,
 
     >>> AggregatorAdvisor = datasets.load_dataset("maomlab/AggregatorAdvisor", name = "AggregatorAdvisor")
     Downloading readme: 100%|██████████| 4.70k/4.70k [00:00<00:00, 277kB/s]
@@ -138,3 +140,6 @@ Split and evaluate the catboost model
         predictions=preds["cat_boost_regressor::logP"])    
 
 ## Citation
+J. Med. Chem. 2015, 58, 17, 7076–7087
+Publication Date:August 21, 2015
+https://doi.org/10.1021/acs.jmedchem.5b01105