Deciphering exogenous chemical carcinogenicity through interpretable deep learning: A novel approach for evaluating atmospheric pollutant hazards
H Zhang, H Yi, Y Hao, L Zhao, W Pan, Q Xue… - Journal of Hazardous …, 2024 - Elsevier
Cancer remains a significant global health concern, with millions of deaths attributed to it
annually. Environmental pollutants play a pivotal role in cancer etiology and contribute to the …
annually. Environmental pollutants play a pivotal role in cancer etiology and contribute to the …
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 …
chemistry and drug development. However, it is a time-consuming and label-intensive …
Predicting environmental chemical carcinogenicity using a hybrid machine-learning approach
S Limbu, S Dakshanamurthy - bioRxiv, 2021 - biorxiv.org
Determining environmental chemical carcinogenicity is an urgent need as humans are
increasingly exposed to these chemicals. In this study, we determined the carcinogenicity of …
increasingly exposed to these chemicals. In this study, we determined the carcinogenicity of …
Deep learning for predicting toxicity of chemicals: a mini review
W Tang, J Chen, Z Wang, H Xie… - Journal of Environmental …, 2018 - Taylor & Francis
Humans and wildlife inhabit a world with panoply of natural and synthetic chemicals.
Alarmingly, only a limited number of chemicals have undergone comprehensive …
Alarmingly, only a limited number of chemicals have undergone comprehensive …
Deep Learning in Environmental Toxicology: Current Progress and Open Challenges
H Tan, J Jin, C Fang, Y Zhang, B Chang… - ACS ES&T …, 2023 - ACS Publications
Ubiquitous chemicals in the environment may pose a threat to human health and the
ecosystem, so comprehensive toxicity information must be obtained. Due to the inability of …
ecosystem, so comprehensive toxicity information must be obtained. Due to the inability of …
Chemical toxicity prediction based on semi-supervised learning and graph convolutional neural network
J Chen, YW Si, CW Un, SWI Siu - Journal of cheminformatics, 2021 - Springer
As safety is one of the most important properties of drugs, chemical toxicology prediction has
received increasing attentions in the drug discovery research. Traditionally, researchers rely …
received increasing attentions in the drug discovery research. Traditionally, researchers rely …
Predicting chemical carcinogens using a hybrid neural network deep learning method
S Limbu, S Dakshanamurthy - Sensors, 2022 - mdpi.com
Determining environmental chemical carcinogenicity is urgently needed as humans are
increasingly exposed to these chemicals. In this study, we developed a hybrid neural …
increasingly exposed to these chemicals. In this study, we developed a hybrid neural …
CapsCarcino: A novel sparse data deep learning tool for predicting carcinogens
YW Wang, L Huang, SW Jiang, K Li, J Zou… - Food and Chemical …, 2020 - Elsevier
Determining chemical carcinogenicity in the early stages of drug discovery is fundamentally
important to prevent the adverse effect of carcinogens on human health. There has been a …
important to prevent the adverse effect of carcinogens on human health. There has been a …
Predicting Dose-Dependent Carcinogenicity of Chemical Mixtures Using a Novel Hybrid Neural Network Framework and Mathematical Approach
S Limbu, S Dakshanamurthy - Toxics, 2023 - mdpi.com
This study addresses the challenge of assessing the carcinogenic potential of hazardous
chemical mixtures, such as per-and polyfluorinated substances (PFASs), which are known to …
chemical mixtures, such as per-and polyfluorinated substances (PFASs), which are known to …
Advancing chemical carcinogenicity prediction modeling: opportunities and challenges
Carcinogenicity assessment of any compound is a laborious and expensive exercise with
several associated ethical and practical concerns. While artificial intelligence (AI) offers …
several associated ethical and practical concerns. While artificial intelligence (AI) offers …