Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

MLRDFM: a multi-view Laplacian regularized DeepFM model for predicting miRNA-disease associations.

Briefings in bioinformatics - 13 May 2022

Ding Yulian, Lei Xiujuan, Liao Bo, Wu Fang-Xiang

Abstract excerpt

MOTIVATION: MicroRNAs (miRNAs), as critical regulators, are involved in various fundamental and vital biological processes, and their abnormalities are closely related to human diseases. Predicting disease-related miRNAs is beneficial to uncovering new biomarkers for the prevention, detection, prognosis, diagnosis and treatment of complex diseases. RESULTS: In this study, we propose a multi-view Laplacian...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to Computational Biology
Share to Genetic Predisposition to Disease

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to MicroRNAs

Source

Identifiers

PMID: 35323901
DOI: 10.1093/bib/bbac079

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 3 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

MLRDFM: a multi-view Laplacian regularized DeepFM model for predicting miRNA-disease associations.PMID 35323901Read ↗

Prediction of miRNA-disease associations by neural network-based deep matrix factorization.Semantic proximity Read ↗

MRDPDA: A multi-Laplacian regularized deepFM model for predicting piRNA-disease associations.Semantic proximity Read ↗

Hessian Regularized [Formula: see text]-Nonnegative Matrix Factorization and Deep Learning for miRNA-Disease Associations Prediction.Semantic proximity Read ↗

DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations.Semantic proximity Read ↗

MDSCMF: Matrix Decomposition and Similarity-Constrained Matrix Factorization for miRNA-Disease Association Prediction.Semantic proximity Read ↗

Predicting miRNA-Disease Associations Based On Multi-View Variational Graph Auto-Encoder With Matrix Factorization.Semantic proximity Read ↗

MicroRNA-disease association prediction by matrix tri-factorization.Semantic proximity Read ↗

HPTRMF: Collaborative Matrix Factorization-Based Prediction Method for LncRNA-Disease Associations Using High-Order Perturbation and Flexible Trifactor Regularization.Semantic proximity Read ↗

A method for miRNA diffusion association prediction using machine learning decoding of multi-level heterogeneous graph Transformer encoded representations.Semantic proximity Read ↗

MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations.Semantic proximity Read ↗

Predicting miRNA-Disease Associations via Combining Probability Matrix Feature Decomposition With Neighbor Learning.Semantic proximity Read ↗

lncRNA-disease association prediction based on optimizing measures of multi-graph regularized matrix factorization.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.