Epigenetic modulation by oncolytic viruses: Implications for cancer therapeutic efficacy

MH Sultan, Q Zhan, H Jin, X Jia, Y Wang - Biochimica et Biophysica Acta …, 2025 - Elsevier
Among various therapeutic agents, Oncolytic Viruses (OVs) are the most promising
anticancer therapeutics because of their tumor-specific targeting and capability to mediate …

Artificial intelligence and deep learning algorithms for epigenetic sequence analysis: A review for epigeneticists and AI experts

M Tahir, M Norouzi, SS Khan, JR Davie… - Computers in Biology …, 2024 - Elsevier
Epigenetics encompasses mechanisms that can alter the expression of genes without
changing the underlying genetic sequence. The epigenetic regulation of gene expression is …

A survey on imbalanced learning: latest research, applications and future directions

W Chen, K Yang, Z Yu, Y Shi, CL Chen - Artificial Intelligence Review, 2024 - Springer
Imbalanced learning constitutes one of the most formidable challenges within data mining
and machine learning. Despite continuous research advancement over the past decades …

Using a hybrid neural network architecture for DNA sequence representation: A study on N4-methylcytosine sites

VN Nguyen, TT Ho, TD Doan, NQK Le - Computers in Biology and Medicine, 2024 - Elsevier
Abstract N 4-methylcytosine (4mC) is a modified form of cytosine found in DNA, contributing
to epigenetic regulation. It exists in various genomes, including the Rosaceae family …

iDNA-ITLM: An interpretable and transferable learning model for identifying DNA methylation

X Yu, C Yani, Z Wang, H Long, R Zeng, X Liu, B Anas… - PloS one, 2024 - journals.plos.org
In this study, from the perspective of image processing, we propose the iDNA-ITLM model,
using a novel data enhance strategy by continuously self-replicating a short DNA sequence …

Transfer Learning in Cancer Genetics, Mutation Detection, Gene Expression Analysis, and Syndrome Recognition

H Ashayeri, N Sobhi, P Pławiak, S Pedrammehr… - Cancers, 2024 - mdpi.com
Simple Summary Transfer learning is a technique utilizing a pre-trained model's knowledge
in a new task. This helps reduce the sample size and time needed for training. These …

Time series-based hybrid ensemble learning model with multivariate multidimensional feature coding for DNA methylation prediction

W Yan, L Tan, L Mengshan, Z Weihong, S Sheng… - BMC genomics, 2023 - Springer
Background DNA methylation is a form of epigenetic modification that impacts gene
expression without modifying the DNA sequence, thereby exerting control over gene …

iDNA-OpenPrompt: OpenPrompt learning model for identifying DNA methylation

X Yu, J Ren, H Long, R Zeng, G Zhang, A Bilal… - Frontiers in …, 2024 - frontiersin.org
Introduction: DNA methylation is a critical epigenetic modification involving the addition of a
methyl group to the DNA molecule, playing a key role in regulating gene expression without …

PSATF-6mA: an integrated learning fusion feature-encoded DNA-6 mA methylcytosine modification site recognition model based on attentional mechanisms

Y Kang, H Wang, Y Qin, G Liu, Y Yu, Y Zhang - Frontiers in Genetics, 2024 - frontiersin.org
DNA methylation is of crucial importance for biological genetic expression, such as
biological cell differentiation and cellular tumours. The identification of DNA-6mA sites using …

GANSamples-ac4C: Enhancing ac4C site prediction via generative adversarial networks and transfer learning

F Li, J Zhang, K Li, Y Peng, H Zhang, Y Xu, Y Yu… - Analytical …, 2024 - Elsevier
Abstract RNA modification, N4-acetylcytidine (ac4C), is enzymatically catalyzed by N-
acetyltransferase 10 (NAT10) and plays an essential role across tRNA, rRNA, and mRNA. It …