Fingerprint-enhanced graph attention network (FinGAT) model for antibiotic discovery

Fingerprint-enhanced graph attention network (FinGAT) model for antibiotic discovery

Artificial Intelligence (AI) techniques are of great potential to fundamentally change antibiotic discovery industries. Efficient and effective molecular featurization is key to all highly accurate learning models for antibiotic discovery. In this paper, we propose a fingerprint-enhanced graph atten...

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Bibliographic Details
Main Authors: Choo, Hou Yee, Wee, Junjie, Shen, Cong, Xia, Kelin
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2023
Subjects:
Science::Mathematics
Anti-bacterial Agents
Artificial Intelligence
Online Access:https://hdl.handle.net/10356/170327
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Institution: Nanyang Technological University
Language: English

Internet

https://hdl.handle.net/10356/170327

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