Graph representation learning in biomedicine and healthcare

MM Li, K Huang, M Zitnik - Nature Biomedical Engineering, 2022 - nature.com
Networks—or graphs—are universal descriptors of systems of interacting elements. In
biomedicine and healthcare, they can represent, for example, molecular interactions …

Association predictions of genomics, proteinomics, transcriptomics, microbiome, metabolomics, pathomics, radiomics, drug, symptoms, environment factor, and …

Y Pan, X Lei, Y Zhang - Medicinal research reviews, 2022 - Wiley Online Library
Currently, the research of multi‐omics, such as genomics, proteinomics, transcriptomics,
microbiome, metabolomics, pathomics, and radiomics, are hot spots. The relationship …

miRNA effects on gut homeostasis: therapeutic implications for inflammatory bowel disease

S Dhuppar, G Murugaiyan - Trends in immunology, 2022 - cell.com
Inflammatory bowel disease (IBD) spans a range of chronic conditions affecting the
gastrointestinal (GI) tract, which are marked by intermittent flare-ups and remissions. IBD …

An effective drug-disease associations prediction model based on graphic representation learning over multi-biomolecular network

H Jiang, Y Huang - BMC bioinformatics, 2022 - Springer
Abstract Background Drug-disease associations (DDAs) can provide important information
for exploring the potential efficacy of drugs. However, up to now, there are still few DDAs …

Emerging role of microRNAs in stroke protection elicited by remote postconditioning

G Pignataro - Frontiers in Neurology, 2021 - frontiersin.org
Remote ischemic conditioning (RIC) represents an innovative and attractive neuroprotective
approach in brain ischemia. The purpose of this intervention is to activate endogenous …

DANE-MDA: Predicting microRNA-disease associations via deep attributed network embedding

BY Ji, ZH You, Y Wang, ZW Li, L Wong - Iscience, 2021 - cell.com
Predicting the microRNA-disease associations by using computational methods is
conductive to the efficiency of costly and laborious traditional bio-experiments. In this study …

DF-MDA: An effective diffusion-based computational model for predicting miRNA-disease association

HY Li, ZH You, L Wang, X Yan, ZW Li - Molecular Therapy, 2021 - cell.com
It is reported that microRNAs (miRNAs) play an important role in various human diseases.
However, the mechanisms of miRNA in these diseases have not been fully understood …

A multi-graph deep learning model for predicting drug-disease associations

BW Zhao, ZH You, L Hu, L Wong, BY Ji… - … Computing Theories and …, 2021 - Springer
Computational drug repositioning is essential in drug discovery and development. The
previous methods basically utilized matrix calculation. Although they had certain effects, they …

Graph representation learning in biomedicine

MM Li, K Huang, M Zitnik - arXiv preprint arXiv:2104.04883, 2021 - arxiv.org
Biomedical networks (or graphs) are universal descriptors for systems of interacting
elements, from molecular interactions and disease co-morbidity to healthcare systems and …

Using sequence similarity based on CKSNP features and a graph neural network model to identify miRNA–disease associations

M Li, Y Fan, Y Zhang, Z Lv - Genes, 2022 - mdpi.com
Among many machine learning models for analyzing the relationship between miRNAs and
diseases, the prediction results are optimized by establishing different machine learning …