%0 Journal Article %1 hastings2021learning %A Hastings, Janna %A Glauer, Martin %A Memariani, Adel %A Neuhaus, Fabian %A Mossakowski, Till %D 2021 %J Journal of Cheminformatics %K extension myown, ontology ontology, %N 23 (2021) %R 10.21203/rs.3.rs-107431/v1 %T Learning chemistry: exploring the suitability of machine learning for the task of structure-based chemical ontology classification. %U https://doi.org/10.1186/s13321-021-00500-8 %V 13

@article{hastings2021learning, added-at = {2020-12-02T17:12:54.000+0100}, author = {Hastings, Janna and Glauer, Martin and Memariani, Adel and Neuhaus, Fabian and Mossakowski, Till}, bdsk-url-1 = {https://doi.org/10.21203/rs.3.rs-107431/v1}, biburl = {https://www.bibsonomy.org/bibtex/25d9d9c85eea491fabc2be70b6151ea71/fneuhaus}, date-added = {2020-12-02 13:08:16 +0100}, date-modified = {2020-12-02 17:01:41 +0100}, doi = {10.21203/rs.3.rs-107431/v1}, interhash = {e35748e1a3f09c42bab2ca5302c7b4bd}, intrahash = {5d9d9c85eea491fabc2be70b6151ea71}, journal = {Journal of Cheminformatics}, keywords = {extension myown, ontology ontology,}, number = {23 (2021)}, timestamp = {2021-11-25T21:47:02.000+0100}, title = {Learning chemistry: exploring the suitability of machine learning for the task of structure-based chemical ontology classification.}, url = {https://doi.org/10.1186/s13321-021-00500-8}, volume = 13, year = 2021 }