Hierarchical graph attention network for miRNA-disease association prediction

Z Li, T Zhong, D Huang, ZH You, R Nie - Molecular Therapy, 2022 - cell.com
Many biological studies show that the mutation and abnormal expression of microRNAs
(miRNAs) could cause a variety of diseases. As an important biomarker for disease …

MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graph

Y Chu, X Wang, Q Dai, Y Wang, Q Wang… - Briefings in …, 2021 - academic.oup.com
Accurate identification of the miRNA-disease associations (MDAs) helps to understand the
etiology and mechanisms of various diseases. However, the experimental methods are …

Recent development of bioinformatics tools for microRNA target prediction

MS Khatun, MA Alam, W Shoombuatong… - Current medicinal …, 2022 - ingentaconnect.com
MicroRNAs (miRNAs) are central players that regulate the post-transcriptional processes of
gene expression. Binding of miRNAs to target mRNAs can repress their translation by …

SMAP: Similarity-based matrix factorization framework for inferring miRNA-disease association

J Ha - Knowledge-Based Systems, 2023 - Elsevier
Background: Based on increasing evidence, microRNAs (miRNAs) play significant roles in
various complex human diseases. Therefore, identifying the disease-related miRNAs could …

Matrix reconstruction with reliable neighbors for predicting potential MiRNA–disease associations

H Feng, D **, J Li, Y Li, Q Zou… - Briefings in Bioinformatics, 2023 - academic.oup.com
Numerous experimental studies have indicated that alteration and dysregulation in
mircroRNAs (miRNAs) are associated with serious diseases. Identifying disease-related …

Survey on Recommender Systems for Biomedical Items in Life and Health Sciences

M Pato, M Barros, FM Couto - ACM Computing Surveys, 2024 - dl.acm.org
The generation of biomedical data is of such magnitude that its retrieval and analysis have
posed several challenges. A survey of recommender system (RS) approaches in biomedical …

Scmfmda: Predicting microrna-disease associations based on similarity constrained matrix factorization

L Li, Z Gao, YT Wang, MW Zhang, JC Ni… - PLoS computational …, 2021 - journals.plos.org
miRNAs belong to small non-coding RNAs that are related to a number of complicated
biological processes. Considerable studies have suggested that miRNAs are closely …

NCMD: Node2vec-based neural collaborative filtering for predicting miRNA-disease association

J Ha, S Park - IEEE/ACM Transactions on Computational …, 2022 - ieeexplore.ieee.org
Numerous studies have reported that micro RNAs (miRNAs) play pivotal roles in disease
pathogenesis based on the deregulation of the expressions of target messenger RNAs …

MSGCL: inferring miRNA–disease associations based on multi-view self-supervised graph structure contrastive learning

X Ruan, C Jiang, P Lin, Y Lin, J Liu… - Briefings in …, 2023 - academic.oup.com
Potential miRNA–disease associations (MDA) play an important role in the discovery of
complex human disease etiology. Therefore, MDA prediction is an attractive research topic …

MDA-CF: predicting miRNA-disease associations based on a cascade forest model by fusing multi-source information

Q Dai, Y Chu, Z Li, Y Zhao, X Mao, Y Wang… - Computers in Biology …, 2021 - Elsevier
MicroRNAs (miRNAs) are significant regulators in various biological processes. They may
become promising biomarkers or therapeutic targets, which provide a new perspective in …