Integration of the Natural Language Processing of Structural Information Simplified Molecular-Input Line-Entry System Can Improve the In Vitro Prediction of Human Skin Sensitizers

Integration of the Natural Language Processing of Structural Information Simplified Molecular-Input Line-Entry System Can Improve the In Vitro Prediction of Human Skin Sensitizers

Natural language processing (NLP) technology has recently used to predict substance properties based on their Simplified Molecular-Input Line-Entry System (SMILES). We aimed to develop a model predicting human skin sensitizers by integrating text features derived from SMILES with in vitro test outco...

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Bibliographic Details
Main Authors: Jae-Hee Kwon, Jihye Kim, Kyung-Min Lim, Myeong Gyu Kim
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Toxics
Subjects:
skin sensitizer
natural language processing
QSAR
SENS-IS
direct peptide reactivity assay (DPRA)
Online Access:https://www.mdpi.com/2305-6304/12/2/153

Internet

https://www.mdpi.com/2305-6304/12/2/153

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