DeepCarc: Deep Learning-Powered Carcinogenicity Prediction Using Model-Level Representation

Carcinogenicity testing plays an essential role in identifying carcinogens in environmental chemistry and drug development. However, it is a time-consuming and label-intensive process to evaluate the carcinogenic potency with conventional 2-years rodent animal studies. Thus, there is an urgent need...

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Detalles Bibliográficos
Autores principales: Li, Ting, Tong, Weida, Roberts, Ruth, Liu, Zhichao, Thakkar, Shraddha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8636933/
https://www.ncbi.nlm.nih.gov/pubmed/34870186
http://dx.doi.org/10.3389/frai.2021.757780

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8636933/
https://www.ncbi.nlm.nih.gov/pubmed/34870186
http://dx.doi.org/10.3389/frai.2021.757780

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