GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure
Main Authors: | Hoyeon Jeong, Young-Rae Cho, Jungsoo Gim, Seung-Kuy Cha, Maengsup Kim, Dae Ryong Kang |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2024-01-01
|
Series: | PLoS ONE |
Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10971776/?tool=EBI |
Similar Items
-
Entropy-Based Graph Clustering of PPI Networks for Predicting Overlapping Functional Modules of Proteins
by: Hoyeon Jeong, et al.
Published: (2021-09-01) -
MHC-II neoantigens shape tumour immunity and response to immunotherapy
by: Luoma, Adrienne M., et al.
Published: (2020) -
Beyond MHC binding: immunogenicity prediction tools to refine neoantigen selection in cancer patients
by: Ibel Carri, et al.
Published: (2023-04-01) -
Applied graph theory : graphs and electrical networks /
by: Chen, Wai-Kai, 1936-
Published: (1976) -
Applying Graph Neural Networks to the Decision Version of Graph Combinatorial Optimization Problems
by: Raka Jovanovic, et al.
Published: (2023-01-01)