Artificial Intelligence Meets Toxicology-Reference-Cited by-同舟云学术

Artificial Intelligence Meets Toxicology

Published:2022-08-15 Issue:8 Volume:35 Page:1289-1290
ISSN:0893-228X
Container-title:Chemical Research in Toxicology
language:en
Short-container-title:Chem. Res. Toxicol.

Author:

Tetko Igor V.¹²^ORCID,Klambauer Günter³,Clevert Djork-Arné⁴,Shah Imran⁵^ORCID,Benfenati Emilio⁶^ORCID

Affiliation:

1. Institute of Structural Biology, Molecular Targets and Therapeutics Center, Helmholtz Munich-Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), 85764 Neuherberg, Germany

2. BIGCHEM GmbH, Valerystr. 49, 85716 Unterschleißheim, Germany

3. ELLIS Unit Linz, LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Altenbergerstraße 69, 4040 Linz, Austria

4. Machine Learning Research, Bayer AG, 13342 Berlin, Germany

5. Center for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States

6. Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milano, Italy

Publisher

American Chemical Society (ACS)

Subject

Toxicology,General Medicine

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.2c00196

Reference6 articles.

1. The rise of deep learning in drug discovery

2. Transformer-CNN: Swiss knife for QSAR modeling and interpretation

3. Img2Mol – accurate SMILES recognition from molecular graphical depictions

4. Combinatorial feature embedding based on CNN and LSTM for biomedical named entity recognition

5. Introduction to Special Issue: Computational Toxicology

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