OLB-AC: toward optimizing ligand bioactivities through deep graph learning and activity cliffs
Motivation: Deep graph learning (DGL) has been widely employed in the realm of ligand-based virtual screening. Within this field, a key hurdle is the existence of activity cliffs (ACs), where minor chemical alterations can lead to significant changes in bioactivity. In response, several DGL models h...
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Main Authors: | Yin, Yueming, Hu, Haifeng, Yang, Jitao, Ye, Chun, Goh, Wilson Wen Bin, Kong, Adams Wai Kin, Wu, Jiansheng |
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Other Authors: | College of Computing and Data Science |
Format: | Article |
Language: | English |
Published: |
2024
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/181726 |
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Institution: | Nanyang Technological University |
Language: | English |
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