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

Identification of miRNA-disease associations via multiple information integration with Bayesian ranking.

Briefings in bioinformatics - 5 Nov 2021

Zhu Chi-Chi, Wang Chun-Chun, Zhao Yan, Zuo Mingcheng, Chen Xing

Abstract excerpt

In recent years, increasing microRNA (miRNA)-disease associations were identified through traditionally biological experiments. These associations contribute to revealing molecular mechanism of diseases and preventing and curing diseases. To improve the efficiency of miRNA-disease association discovery, some calculation methods were developed as auxiliary tools for researchers. In the current study, we raised a...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Bayes Theorem
Share to Computational Biology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Computer Simulation

Share to Genetic Predisposition to Disease

Share to MicroRNAs

Share to Neoplasms

Source

Identifiers

PMID: 34347021
DOI: 10.1093/bib/bbab302

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

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

Identification of miRNA-disease associations via multiple information integration with Bayesian ranking.PMID 34347021Read ↗

RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction.Semantic proximity Read ↗

WBSMDA: Within and Between Score for MiRNA-Disease Association prediction.Semantic proximity Read ↗

A novel computational model based on super-disease and miRNA for potential miRNA-disease association prediction.Semantic proximity Read ↗

PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction.Semantic proximity Read ↗

ELLPMDA: Ensemble learning and link prediction for miRNA-disease association prediction.Semantic proximity Read ↗

NARRMDA: negative-aware and rating-based recommendation algorithm for miRNA-disease association prediction.Semantic proximity Read ↗

BLNIMDA: identifying miRNA-disease associations based on weighted bi-level network.Semantic proximity Read ↗

Large-scale prediction of microRNA-disease associations by combinatorial prioritization algorithm.Semantic proximity Read ↗

Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.Semantic proximity Read ↗

NDAMDA: Network distance analysis for MiRNA-disease association prediction.Semantic proximity Read ↗

RBMMMDA: predicting multiple types of disease-microRNA associations.Semantic proximity Read ↗

EGBMMDA: Extreme Gradient Boosting Machine for MiRNA-Disease Association prediction.Semantic proximity Read ↗

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