SkinSensPred as a Promising in Silico Tool for Integrated Testing Strategy on Skin Sensitization
Abstract
:1. Introduction
2. Materials and Methods
2.1. Dataset
2.2. ITS-SkinSensPred
2.3. Performance
3. Results and Discussion
3.1. Hazard Identification
3.2. Potency Prediction
3.3. Classification of Mixtures of Agrochemicals
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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LLNA (n = 168) | Human (n = 66) | |||||||
---|---|---|---|---|---|---|---|---|
Method | Balanced Accuracy (%) | Sensitivity (%) | Specificity (%) | Coverage (%) | Balanced Accuracy (%) | Sensitivity (%) | Specificity (%) | Coverage (%) |
2o3 * | 84 | 82 | 85 | 80 | 88 | 89 | 88 | 83 |
ITSv1 * | 81 | 92 | 70 | 95 | 69 | 93 | 44 | 97 |
ITSv2 * | 80 | 93 | 67 | 93 | 69 | 94 | 44 | 94 |
ITS-SkinSensPred | 80 | 88 | 72 | 96 | 70 | 94 | 45 | 91 |
LLNA * | - | - | - | - | 58 | 94 | 22 | 85 |
LLNA (n = 156) | Human (n = 63) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Method | Coverage (%) | Overall (%) | 1A (%) | 1B (%) | NC (%) | Coverage (%) | Overall (%) | 1A (%) | 1B (%) | NC (%) |
ITSv1 * | 94 | 71 | 74 | 71 | 70 | 95 | 68 | 65 | 77 | 44 |
ITSv2 * | 90 | 71 | 72 | 72 | 67 | 90 | 70 | 67 | 80 | 44 |
ITS-SkinSensPred | 94 | 71 | 73 | 69 | 72 | 89 | 70 | 67 | 81 | 45 |
LLNA * | - | - | - | - | - | 75 | 60 | 56 | 74 | 25 |
Method | Balanced Accuracy (%) | Sensitivity (%) | Specificity (%) | Coverage (%) |
---|---|---|---|---|
2o3 * | 78 | 90 | 67 | 70 |
ITSv2 * | 57 | 91 | 23 | 89 |
ITS-SkinSensPred | 61 | 89 | 33 | 67 |
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Wang, S.-S.; Wang, C.-C.; Tung, C.-W. SkinSensPred as a Promising in Silico Tool for Integrated Testing Strategy on Skin Sensitization. Int. J. Environ. Res. Public Health 2022, 19, 12856. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191912856
Wang S-S, Wang C-C, Tung C-W. SkinSensPred as a Promising in Silico Tool for Integrated Testing Strategy on Skin Sensitization. International Journal of Environmental Research and Public Health. 2022; 19(19):12856. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191912856
Chicago/Turabian StyleWang, Shan-Shan, Chia-Chi Wang, and Chun-Wei Tung. 2022. "SkinSensPred as a Promising in Silico Tool for Integrated Testing Strategy on Skin Sensitization" International Journal of Environmental Research and Public Health 19, no. 19: 12856. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191912856