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

EMCMDA: predicting miRNA-disease associations via efficient matrix completion.

Scientific reports - 4 Jun 2024

Qin Chao, Zhang Jiancheng, Ma Lingyu

Abstract excerpt

Abundant researches have consistently illustrated the crucial role of microRNAs (miRNAs) in a wide array of essential biological processes. Furthermore, miRNAs have been validated as promising therapeutic targets for addressing complex diseases. Given the costly and time-consuming nature of traditional biological experimental validation methods, it is imperative to develop computational methods. In the work, we...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Breast Neoplasms
Share to Computational Biology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genetic Predisposition to Disease

Share to MicroRNAs

Source

Open in PubMed Open full text

Identifiers

PMID: 38834687
DOI: 10.1038/s41598-024-63582-y
PMCID: PMC11150514

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

EMCMDA: predicting miRNA-disease associations via efficient matrix completion.PMID 38834687Read ↗

MDAlmc: A Novel Low-rank Matrix Completion Model for MiRNADisease Association Prediction by Integrating Similarities among MiRNAs and Diseases.Semantic proximity Read ↗

NCMCMDA: miRNA-disease association prediction through neighborhood constraint matrix completion.Semantic proximity Read ↗

Improved Prediction of miRNA-Disease Associations Based on Matrix Completion with Network Regularization.Semantic proximity Read ↗

Integrating lncRNA data for prediction of miRNA-disease association using network fusion and matrix completion.Semantic proximity Read ↗

IMC-MDA: Prediction of miRNA-disease association based on induction matrix completion.Semantic proximity Read ↗

MCMDA: Matrix completion for MiRNA-disease association prediction.Semantic proximity Read ↗

Prediction of miRNA-disease association based on multisource inductive matrix completion.Semantic proximity Read ↗

Predicting miRNA-disease association based on inductive matrix completion.Semantic proximity Read ↗

Improved low-rank matrix recovery method for predicting miRNA-disease association.Semantic proximity Read ↗

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

miRCom: Tensor Completion Integrating Multi-View Information to Deduce the Potential Disease-Related miRNA-miRNA Pairs.Semantic proximity Read ↗

NFMCLDA: Predicting miRNA-based lncRNA-disease associations by network fusion and matrix completion.Semantic proximity Read ↗

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