Update README.md
Browse files
README.md
CHANGED
|
@@ -38,4 +38,11 @@ model = BertModel.from_pretrained(checkpoint)
|
|
| 38 |
example = 'O=C([C@@H](c1ccc(cc1)O)N)N[C@@H]1C(=O)N2[C@@H]1SC([C@@H]2C(=O)O)(C)C'
|
| 39 |
tokens = tokenizer(example, return_tensors='pt')
|
| 40 |
predictions = model(**tokens)
|
| 41 |
-
```
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 38 |
example = 'O=C([C@@H](c1ccc(cc1)O)N)N[C@@H]1C(=O)N2[C@@H]1SC([C@@H]2C(=O)O)(C)C'
|
| 39 |
tokens = tokenizer(example, return_tensors='pt')
|
| 40 |
predictions = model(**tokens)
|
| 41 |
+
```
|
| 42 |
+
|
| 43 |
+
## Research
|
| 44 |
+
- Jouary et al. (2025) [Bridging scales between chemical space and behavioral phenotype](https://openreview.net/forum?id=DJI46O06tF):
|
| 45 |
+
|
| 46 |
+
A cross-modal mapping between behavior and molecular structure, derived using the **unikei/bert-base-smiles** model, effectively distinguished between distinct neurotransmitter classes, such as dopaminergic/serotonergic ligands, purines, and metabotropic glutamate ligands.
|
| 47 |
+
|
| 48 |
+
|