SPRDA: a link prediction approach based on the structural perturbation to infer disease-associated Piwi-interacting RNAs
Abstract piRNA and PIWI proteins have been confirmed for disease diagnosis and treatment
as novel biomarkers due to its abnormal expression in various cancers. However, the …
as novel biomarkers due to its abnormal expression in various cancers. However, the …
Ichrom-deep: an attention-based deep learning model for identifying chromatin interactions
P Zhang, H Wu - IEEE Journal of Biomedical and Health …, 2023 - ieeexplore.ieee.org
Identification of chromatin interactions is crucial for advancing our knowledge of gene
regulation. However, due to the limitations of high-throughput experimental techniques …
regulation. However, due to the limitations of high-throughput experimental techniques …
AMDECDA: attention mechanism combined with data ensemble strategy for predicting CircRNA-disease association
Accumulating evidence from recent research reveals that circRNA is tightly bound to human
complex disease and plays an important regulatory role in disease progression. Identifying …
complex disease and plays an important regulatory role in disease progression. Identifying …
Community graph convolution neural network for alzheimer's disease classification and pathogenetic factors identification
XA Bi, K Chen, S Jiang, S Luo, W Zhou… - … on Neural Networks …, 2023 - ieeexplore.ieee.org
As a complex neural network system, the brain regions and genes collaborate to effectively
store and transmit information. We abstract the collaboration correlations as the brain region …
store and transmit information. We abstract the collaboration correlations as the brain region …
RPI-CapsuleGAN: Predicting RNA-protein interactions through an interpretable generative adversarial capsule network
ABSTRACT RNA-protein interactions (RPI) play a crucial regulatory role in cellular
physiological processes. The study and prediction of RPIs can be insightful for exploring …
physiological processes. The study and prediction of RPIs can be insightful for exploring …
GSLCDA: an unsupervised deep graph structure learning method for predicting CircRNA-disease association
Growing studies reveal that Circular RNAs (circRNAs) are broadly engaged in physiological
processes of cell proliferation, differentiation, aging, apoptosis, and are closely associated …
processes of cell proliferation, differentiation, aging, apoptosis, and are closely associated …
Drug repositioning via multi-view representation learning with heterogeneous graph neural network
L Peng, C Yang, J Yang, Y Tu, Q Yu, Z Li… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Exploring simple and efficient computational methods for drug repositioning has emerged as
a popular and compelling topic in the realm of comprehensive drug development. The crux …
a popular and compelling topic in the realm of comprehensive drug development. The crux …
DeepCMI: a graph-based model for accurate prediction of circRNA–miRNA interactions with multiple information
Recently, the role of competing endogenous RNAs in regulating gene expression through
the interaction of microRNAs has been closely associated with the expression of circular …
the interaction of microRNAs has been closely associated with the expression of circular …
BEROLECMI: a novel prediction method to infer circRNA-miRNA interaction from the role definition of molecular attributes and biological networks
Abstract Circular RNA (CircRNA)–microRNA (miRNA) interaction (CMI) is an important
model for the regulation of biological processes by non-coding RNA (ncRNA), which …
model for the regulation of biological processes by non-coding RNA (ncRNA), which …
[HTML][HTML] CircRNA-based therapeutics: Current opinions and clinical potential
H Liu, X Yao, Y Zhou, L Chen - The Innovation Medicine, 2024 - the-innovation.org
Circular RNAs (circRNAs) are single-stranded, covalently closed RNA molecules that
perform diverse roles in various cellular processes and have been implicated in many …
perform diverse roles in various cellular processes and have been implicated in many …