data.md

 # Source data
 
-The CC benefits from many resources. The following is an extensive list of resources that are worth considering. Not all of them are currently incorporated in the CC.
+The CC capitalizes on many data sources. The following is an extensive list of resources that are worth considering in current and future versions of the CC. Inside each CC level, I list the resources in **alphabetical order**.
 
 ## Observational data resources
 
-### A. Chemistry
-
-* [X] RDKIT
-* [ ] DeepChem
-* [ ] ChemoPy
-* [X] E3FP
-* [ ] 
-* [ ] Hierarchy
-* [ ] BLOCKS
-
-### B. Targets
+### `A` Chemistry
+
+* [ ] ChemoPy [[paper](https://academic.oup.com/bioinformatics/article/29/8/1092/233093) [code]( http://code.google.com/p/pychem/downloads/list)]
+ * A small chemoinformatics library focused on physicochemical properties and some fingerprints.
+* [ ] DeepChem [[web](http://deepchem.io) [code](https://deepchem.io/docs/deepchem.html)]
+ * A powerful deep learning chemoinformatics library, containing a large number of featurizers.
+ * Among the interesting featurizers, there are the PDB-crystal embeddings, which should, in principle, enable connectivity between crystals and small molecules.
+* [X] E3FP [[paper](https://pubs.acs.org/doi/10.1021/acs.jmedchem.7b00696) [code](https://github.com/keiserlab/e3fp)]
+ * Simple representations of 3D molecular structure.
+ * Integrated tightly with RDKIT.
+* [ ] molBLOCKS [[paper](https://academic.oup.com/bioinformatics/article/30/14/2081/2391178) [code](http://compbio.cs.princeton.edu/molblocks)]
+ * Decompose small molecules into fragments (scaffolds).
+* [ ] PyBioMed [[paper](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861255/) [code]( http://projects.scbdd.com/pybiomed.html)]
+ * A number of physicochemical descriptors and the common fingerprints. Very similar to ChemoPy.
+ * It can also featurize sequence data (protein and DNA).
+* [X] RDKIT [[paper]() [code](https://www.rdkit.org/)]
+ * The standard library for chemoinformatics in `python`.
+ * Calculates several fingerprints and also does 3D conformational sampling. 
+
+### `B` Targets
 
 * [X] DrugBank mode of action and metabolic genes
 * [X] ChEMBL
@@ -27,7 +36,7 @@ The CC benefits from many resources. The following is an extensive list of resou
 * [ ] Touchstone binding data
 * [ ] Human Metabolome Database
 
-### C. Networks
+### `C` Networks
 
 * [X] Chemical Entities of Biological Interest ([ChEBI]())
 * [X] MetaPhORS
@@ -39,7 +48,7 @@ The CC benefits from many resources. The following is an extensive list of resou
 * [X] KEGG
 
 
-### D. Cells
+### `D` Cells
 
 * [ ] Genomics of Cell Sensitivity in Cancer ([GDSC]())
 * [ ] Cancer Cell Line Enciclopedia ([CCLE]())
@@ -48,7 +57,7 @@ The CC benefits from many resources. The following is an extensive list of resou
 * [ ] 
 
 
-### E. Clinics
+### `E` Clinics
 
 * [X]