A Semi-supervised Graph Deep Neural Network for Automatic Protein Function Annotation-Reference-Cited by-同舟云学术

A Semi-supervised Graph Deep Neural Network for Automatic Protein Function Annotation

Published:2022 Issue: Volume: Page:153-166
ISSN:0302-9743
Container-title:Bioinformatics and Biomedical Engineering
language:
Short-container-title:

Author:

Sellami Akrem^ORCID,Sarker Bishnu^ORCID,Tabbone Salvatore^ORCID,Devignes Marie-Dominique^ORCID,Aridhi Sabeur^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-07802-6_14

Reference23 articles.

1. Aridhi, S., Nguifo, E.M.: Big graph mining: frameworks and techniques. Big Data Res. 6, 1–10 (2016)

2. Cao, Y., Shen, Y.: Tale: transformer-based protein function annotation with joint sequence-label embedding. Bioinformatics 37(18), 2825–2833 (2021)

3. Consortium, U.: UniProt: a hub for protein information. Nucleic Acids Res. 43(D1), D204–D212 (2015)

4. Defferrard, M., Bresson, X., Vandergheynst, P.: Convolutional neural networks on graphs with fast localized spectral filtering. Adv. Neural. Inf. Process. Syst. 29, 3844–3852 (2016)

5. Dohan, D., Gane, A., Bileschi, M.L., Belanger, D., Colwell, L.: Improving protein function annotation via unsupervised pre-training: robustness, efficiency, and insights. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pp. 2782–2791 (2021)

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advanced graph deep learning for High-dimensional image analysis: challenges and opportunities;2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP);2024-07-11

2. Geometric Deep Learning Techniques for Analyzing Brain 3D Meshes;2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP);2024-07-11