AL4PFAS is suite of datasets and software workflow for modeling chemical toxicity with a focus on the “forever chemicals” Per- and polyfluoroalkyl substances (PFAS). To address the scarcity of PFAS toxicity data, a deep “transfer learning” method has been investigated by leveraging toxicity information over the entire organic chemical domain and an uncertainty-informed workflow by incorporating SelectiveNet architecture, which can support future guidance of high throughput screening with knowledge of chemical structures, has been developed.

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Read the paper at : JCIM