Update readme

README.md

@@ -9,6 +9,10 @@ metrics:
 tags:
 - biology
 - chemistry
+- therapeutic science
+- drug design
+- drug development
+- therapeutics
 library_name: tdc
 license: bsd-2-clause
 ---
@@ -17,18 +21,13 @@ license: bsd-2-clause
 
 The CYP P450 genes are involved in the formation and breakdown (metabolism) of various molecules and chemicals within cells. Specifically, CYP3A4 is an important enzyme in the body, mainly found in the liver and in the intestine. It oxidizes small foreign organic molecules (xenobiotics), such as toxins or drugs, so that they can be removed from the body.
 
-
-
 ## Task description
 Binary classification. Given a drug SMILES string, predict CYP3A4 inhibition.
 
-
-
-
 ## Dataset statistics
 Total: 12,328 drugs
 
-## Dataset split: 
+## Dataset split
 Random split on 70% training, 10% validation, and 20% testing
 To load the dataset in TDC, type
 ```python
@@ -38,7 +37,7 @@ data = ADME(name = 'CYP3A4_Veith')
 
 ## Model description
 
-AttentiveFP is a Graph Attention Network-based molecular representation learning method. Model is tuned with 100 runs using Ax platform.
+AttentiveFP is a Graph Attention Network-based molecular representation learning method. The model is tuned with 100 runs using the Ax platform.
 
 ```python
 from tdc import tdc_hf_interface
@@ -48,5 +47,6 @@ dp_model = tdc_hf_herg.load_deeppurpose('./data')
 tdc_hf.predict_deeppurpose(dp_model, ['YOUR SMILES STRING'])
 ```
 
-## References:
-[1] Veith, Henrike et al. “Comprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries.” Nature biotechnology vol. 27,11 (2009): 1050-5.
+## References
+* Dataset entry in Therapeutics Data Commons, https://tdcommons.ai/single_pred_tasks/adme/#cyp-p450-3a4-inhibition-veith-et-al
+* Veith, Henrike et al. “Comprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries.” Nature Biotechnology vol. 27,11 (2009): 1050-5.