Predicting Aromatic Amine Mutagenicity with Confidence: A Case Study Using Conformal Prediction.
The occurrence of mutagenicity in primary aromatic amines has been investigated using conformal prediction. The results of the investigation show that it is possible to develop mathematically proven valid models using conformal prediction and that the existence of uncertain classes of prediction, such as both (both classes assigned to a compound) and empty (no class assigned to a compound), provides the user with additional information on how to use, further develop, and possibly improve future models. The study also indicates that the use of different sets of fingerprints results in models, for which the ability to discriminate varies with respect to the set level of acceptable errors.
['Norinder|Ulf|U|0000-0003-3107-331X', 'Myatt|Glenn|G|', 'Ahlberg|Ernst|E|']
D000588:Amines D008968:Molecular Conformation D009153:Mutagens D021281:Quantitative Structure-Activity Relationship
aromatic amines mutagenicity confidence conformal prediction random forest