update

model_cards/article.md

@@ -2,13 +2,13 @@
 
 
 ### ClinTox
-A [ToxSmi model](https://github.com/PaccMann/toxsmi) trained on [ClinTox](https://moleculenet.org/datasets-1) dataset which has two endpoints: Probability of FDA approval and Probability of failure in clinical trials. When using this model, please cite *Born et al. (2023)* (citation below).
+A [ToxSmi model](https://github.com/PaccMann/toxsmi) trained on [ClinTox](https://moleculenet.org/datasets-1) dataset which has two endpoints: Probability of FDA approval and Probability of failure in clinical trials. For details see [Born et al., (2023; *Digital Discovery*)](https://pubs.rsc.org/en/content/articlelanding/2023/dd/d2dd00099g)
 
 ### SIDER
-A [ToxSmi model](https://github.com/PaccMann/toxsmi) trained on the [SIDER](https://moleculenet.org/datasets-1) dataset for 27 different types of side effects of drugs. When using this model, please cite *Born et al. (2023)* (citation below).
+A [ToxSmi model](https://github.com/PaccMann/toxsmi) trained on the [SIDER](https://moleculenet.org/datasets-1) dataset for 27 different types of side effects of drugs. For details see [Born et al., (2023; *Digital Discovery*)](https://pubs.rsc.org/en/content/articlelanding/2023/dd/d2dd00099g)
 
 ### Tox21
-A [ToxSmi model](https://github.com/PaccMann/toxsmi) trained on the [Tox21](https://tripod.nih.gov/tox/) dataset with 12 different types of environmental toxicities. When using this model, please cite *Born et al. (2023)* (citation below).
+A [ToxSmi model](https://github.com/PaccMann/toxsmi) trained on the [Tox21](https://tripod.nih.gov/tox/) dataset with 12 different types of environmental toxicities. For details see [Born et al., (2023; *Digital Discovery*)](https://pubs.rsc.org/en/content/articlelanding/2023/dd/d2dd00099g)
 
 ### SCScore
 Predict the synthetic complexity score (SCScore) as presented in [Coley et al. (*J. Chem. Inf. Model.*; 2018)](https://pubs.acs.org/doi/full/10.1021/acs.jcim.7b00622).
@@ -47,10 +47,14 @@ Calculated with [RDKit](https://www.rdkit.org/docs/source/rdkit.Chem.rdchem.html
 ### ToxSmi citation
 ```bib
 @article{born2023chemical,
-  title={Chemical representation learning for toxicity prediction},
-  author={Born, Jannis and Markert, Greta and Janakarajan, Nikita and Kimber, Talia B. and Volkamer, Andrea and Rodriguez Martinez, Maria and Manica, Matteo},
-  journal={Under review at Digital Discovery},
-  year={2023}
+    author = {Born, Jannis and Markert, Greta and Janakarajan, Nikita and Kimber, Talia B. and Volkamer, Andrea and Martínez, María Rodríguez and Manica, Matteo},
+    title = {Chemical representation learning for toxicity prediction},
+    journal = {Digital Discovery},
+    year = {2023},
+    pages = {-},
+    publisher = {RSC},
+    doi = {10.1039/D2DD00099G},
+    url = {http://dx.doi.org/10.1039/D2DD00099G}
 }
 ```