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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
Published on: February 23, 2024
Artificial intelligence approaches for molecular representation in drug response prediction
Cui-Xiang Lin1, Yuanfang Guan2, Hong-Dong Li3
1School of Mathematics and Computational Science, Xiangtan University, Xiangtan, 411105, Hunan Province, PR China.
Abstract:
Drug response prediction is essential for drug development and disease treatment. One key question in predicting drug response is the representation of molecules, which has been greatly advanced by artificial intelligence (AI) techniques in recent years. In this review, we first describe different types of representation methods, pinpointing their key principles and discussing their limitations. Thereafter we discuss potential ways how these methods could be further developed. We expect that this review will provide useful guidance for researchers in the community.
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