Overview of methods for characterization and visualization of a protein–protein interaction network in a multi-omics integration context

V Robin, A Bodein, MP Scott-Boyer… - Frontiers in Molecular …, 2022 - frontiersin.org
At the heart of the cellular machinery through the regulation of cellular functions, protein–
protein interactions (PPIs) have a significant role. PPIs can be analyzed with network …

A many‐objective optimization‐based local tensor factorization model for skin cancer detection

H Zhao, J Wen, J Yang, X Cai… - … and Computation: Practice …, 2024 - Wiley Online Library
Exploring the associations between microRNAs (miRNAs) and diseases can identify
potential disease features. Prediction of miRNA‐skin cancer associations has become an …

Improving miRNA disease association prediction accuracy using integrated similarity information and deep autoencoders

S Sujamol, ER Vimina… - IEEE/ACM Transactions …, 2022 - ieeexplore.ieee.org
MicroRNAs (miRNAs) are short endogenous non-encoding RNA molecules (22nt) that have
a vital role in many biological and molecular processes inside the human body. Abnormal …

[PDF][PDF] iCluF: an unsupervised iterative cluster-fusion method for patient stratification using multiomics data

SK Shakyawar, BR Sajja, JC Patel… - Bioinformatics …, 2024 - academic.oup.com
Motivation Patient stratification is crucial for the effective treatment or management of
heterogeneous diseases, including cancers. Multiomic technologies facilitate molecular …

[HTML][HTML] CFMKGATDDA: A new collaborative filtering and multiple kernel graph attention network-based method for predicting drug-disease associations

DH Vu, TKP Pham, TH Dang - Intelligence-Based Medicine, 2025 - Elsevier
Drug-disease association prediction is increasingly recognized as crucial for a
comprehensive understanding of the functions and mechanisms of drugs. However, the …

AE-RW: Predicting miRNA-disease associations by using autoencoder and random walk on miRNA-gene-disease heterogeneous network

P Lu, J Jiang - Computational Biology and Chemistry, 2024 - Elsevier
Since scientific investigations have demonstrated that aberrant expression of miRNAs brings
about the incidence of numerous intricate diseases, precise determination of miRNA …

Drug-Disease Association Prediction Through Multiple Integrated Similarities and Deep Learning

TT Van Thai, TTH Duong, DH Tran - 2023 15th International …, 2023 - ieeexplore.ieee.org
The new drugs' development is a time-consuming, laborious, and costly process.
Consequently, the need for computational methods to predict drug-disease associations has …

A survey on computational methods for investigation on ncRNA-disease association through the mode of action perspective

D Bang, J Gu, J Park, D Jeong, B Koo, J Yi… - International Journal of …, 2022 - mdpi.com
Molecular and sequencing technologies have been successfully used in decoding
biological mechanisms of various diseases. As revealed by many novel discoveries, the role …

Predicting Drug-Disease Associations Based on Integrated Similarities and Weighted Bi-level Network

VT Nguyen, H Vu Duc, Y Vu Minh… - … on Advances in …, 2023 - Springer
It is a time-consuming, laborious, and costly process to develop new drugs. Consequently,
develo** computational methods for drug repositioning by predicting drug-disease …

Inferring pseudogene–MiRNA associations based on an ensemble learning framework with similarity kernel fusion

C Fan, M Ding - Scientific Reports, 2023 - nature.com
Accumulating evidence shows that pseudogenes can function as microRNAs (miRNAs)
sponges and regulate gene expression. Mining potential interactions between pseudogenes …