GNNGLY: Graph Neural Networks for Glycan Classification-Reference-Cited by-同舟云学术

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GNNGLY: Graph Neural Networks for Glycan Classification

Published:2023 Issue: Volume:11 Page:51838-51847
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Alkuhlani Alhasan¹^ORCID,Gad Walaa²^ORCID,Roushdy Mohamed³,Salem Abdel-Badeeh M.²

Affiliation:

1. Faculty of Computer and Information Technology, Sana’a University, Sana’a, Yemen

2. Faculty of Computer and Information Science, Ain Shams University, Cairo, Egypt

3. Faculty of Computers and Information Technology, Future University in Egypt, New Cairo, Egypt

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10135098.pdf?arnumber=10135098

Reference27 articles.

1. Chemi-Net: A Molecular Graph Convolutional Network for Accurate Drug Property Prediction

2. Graph Convolutional Networks for Drug Response Prediction

3. Database fingerprint (DFP): an approach to represent molecular databases

4. GlyLES: Grammar-based Parsing of Glycans from IUPAC-condensed to SMILES

5. Examining COVID-19 forecasting using spatio-temporal graph neural networks;kapoor;arXiv 2007 03113,2020

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2. ICT for disaster-resilient education and training;2023-09-12

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