[HTML][HTML] Targeting non-coding RNAs: Perspectives and challenges of in-silico approaches

R Rocca, K Grillone, EL Citriniti, G Gianmarco… - European Journal of …, 2023 - Elsevier
The growing information currently available on the central role of non-coding RNAs
(ncRNAs) including microRNAs (miRNAS) and long non-coding RNAs (lncRNAs) for chronic …

Machine learning strategies in microRNA research: bridging genome to phenome

S Daniel Thomas, K Vijayakumar, L John… - OMICS: A Journal of …, 2024 - liebertpub.com
MicroRNAs (miRNAs) have emerged as a prominent layer of regulation of gene expression.
This article offers the salient and current aspects of machine learning (ML) tools and …

AMDECDA: attention mechanism combined with data ensemble strategy for predicting CircRNA-disease association

L Wang, L Wong, ZH You… - IEEE Transactions on Big …, 2023 - ieeexplore.ieee.org
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 …

BCMCMI: a fusion model for predicting circRNA-miRNA interactions combining semantic and meta-path

MM Wei, CQ Yu, LP Li, ZH You… - Journal of Chemical …, 2023 - ACS Publications
More and more evidence suggests that circRNA plays a vital role in generating and treating
diseases by interacting with miRNA. Therefore, accurate prediction of potential circRNA …

[HTML][HTML] GcForest-based compound-protein interaction prediction model and its application in discovering small-molecule drugs targeting CD47

W Shan, L Chen, H Xu, Q Zhong, Y Xu, H Yao… - Frontiers in …, 2023 - frontiersin.org
Identifying compound–protein interaction plays a vital role in drug discovery. Artificial
intelligence (AI), especially machine learning (ML) and deep learning (DL) algorithms, are …

Graph reasoning method based on affinity identification and representation decoupling for predicting lncRNA-disease associations

S Wang, C Hui, T Zhang, P Wu… - Journal of Chemical …, 2023 - ACS Publications
An increasing number of studies have shown that dysregulation of lncRNAs is related to the
occurrence of various diseases. Most of the previous methods, however, are designed …

Overcoming low adherence to chronic medications by improving their effectiveness using a personalized second-generation digital system

A Bayatra, R Nasserat, Y Ilan - Current Pharmaceutical …, 2024 - ingentaconnect.com
Introduction: Low adherence to chronic treatment regimens is a significant barrier to
improving clinical outcomes in patients with chronic diseases. Low adherence is a result of …

AntiViralDL: Computational Antiviral Drug Repurposing Using Graph Neural Network and Self-Supervised Learning

P Zhang, X Hu, G Li, L Deng - IEEE Journal of Biomedical and …, 2023 - ieeexplore.ieee.org
Viral infections have emerged as significant public health concerns for decades. Antiviral
drugs, specifically designed to combat these infections, have the potential to reduce the …

[HTML][HTML] Machine learning based biomarker discovery for chronic kidney disease–mineral and bone disorder (CKD-MBD)

Y Li, Y Lou, M Liu, S Chen, P Tan, X Li, H Sun… - BMC Medical Informatics …, 2024 - Springer
Introduction Chronic kidney disease-mineral and bone disorder (CKD-MBD) is characterized
by bone abnormalities, vascular calcification, and some other complications. Although there …

Investigation on the antipyretic mechanism of Chaiqin Qingning capsule for the treatment of fever based on network pharmacology, molecular docking, and in vitro …

L Huang, Z Chen, H Gao, Z Wang… - Chemical Biology & …, 2024 - Wiley Online Library
Abstract Chaiqin Qingning Capsule (CQQNC), a traditional Chinese patent medicine, can
effectively shorten the duration of fever and significantly improve fever symptoms. However …