Accurately identifying hemagglutinin using sequence information and machine learning methods

X Zou, L Ren, P Cai, Y Zhang, H Ding, K Deng… - Frontiers in …, 2023‏ - frontiersin.org
Introduction Hemagglutinin (HA) is responsible for facilitating viral entry and infection by
promoting the fusion between the host membrane and the virus. Given its significance in the …

GenoM7GNet: An Efficient N7-Methylguanosine Site Prediction Approach Based on a Nucleotide Language Model

C Li, H Wang, Y Wen, R Yin, X Zeng… - IEEE/ACM Transactions …, 2024‏ - ieeexplore.ieee.org
N-methylguanosine (m7G), one of the mainstream post-transcriptional RNA modifications,
occupies an exceedingly significant place in medical treatments. However, classic …

MetaFluAD: meta-learning for predicting antigenic distances among influenza viruses

Q Jia, Y **a, F Dong, W Li - Briefings in Bioinformatics, 2024‏ - academic.oup.com
Influenza viruses rapidly evolve to evade previously acquired human immunity. Maintaining
vaccine efficacy necessitates continuous monitoring of antigenic differences among strains …

PREDAC-CNN: predicting antigenic clusters of seasonal influenza A viruses with convolutional neural network

J Meng, J Liu, W Song, H Li, J Wang… - Briefings in …, 2024‏ - academic.oup.com
Vaccination stands as the most effective and economical strategy for prevention and control
of influenza. The primary target of neutralizing antibodies is the surface antigen …

TfrAdmCov: a robust transformer encoder based model with Adam optimizer algorithm for COVID-19 mutation prediction

M Burukanli, N Yumuşak - Connection Science, 2024‏ - Taylor & Francis
The development of vaccines and drugs is very important in combating the coronavirus
disease 2019 (COVID-19) virus. The effectiveness of these developed vaccines and drugs …

MAIVeSS: streamlined selection of antigenically matched, high-yield viruses for seasonal influenza vaccine production

C Gao, F Wen, M Guan, B Hatuwal, L Li… - Nature …, 2024‏ - nature.com
Vaccines are the main pharmaceutical intervention used against the global public health
threat posed by influenza viruses. Timely selection of optimal seed viruses with matched …

Prediction of antigenic distance in influenza a using attribute network embedding

F Peng, Y **a, W Li - Viruses, 2023‏ - mdpi.com
Owing to the rapid changes in the antigenicity of influenza viruses, it is difficult for humans to
obtain lasting immunity through antiviral therapy. Hence, tracking the dynamic changes in …

A framework for predicting variable-length epitopes of human-adapted viruses using machine learning methods

R Yin, X Zhu, M Zeng, P Wu, M Li… - Briefings in …, 2022‏ - academic.oup.com
The coronavirus disease 2019 pandemic has alerted people of the threat caused by viruses.
Vaccine is the most effective way to prevent the disease from spreading. The interaction …

Clcap: contrastive learning improves antigenicity prediction for influenza a virus using convolutional neural networks

R Yin, B Ye, J Bian - Methods, 2023‏ - Elsevier
Influenza viruses are detected year-round over the world and the viruses will usually
circulate during fall and winter, causing the seasonal flu. The growing novel variants of …

2D-convolutional neural network based fault detection and classification of transmission lines using scalogram images

P Nayak, SR Das, RK Mallick, S Mishra, A Althobaiti… - Heliyon, 2024‏ - cell.com
The reliable operation of power transmission systems is essential for maintaining the
stability and efficiency of the electrical grid. Rapid and accurate detection of faults in …