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

Identifying human microRNA-disease associations by a new diffusion-based method.

Journal of bioinformatics and computational biology - 1 Aug 2015

Liao Bo, Ding Sumei, Chen Haowen, Li Zejun, Cai Lijun

Abstract excerpt

Identifying the microRNA-disease relationship is vital for investigating the pathogenesis of various diseases. However, experimental verification of disease-related microRNAs remains considerable challenge to many researchers, particularly for the fact that numerous new microRNAs are discovered every year. As such, development of computational methods for disease-related microRNA prediction has recently gained...

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 Databases, Genetic

Share to Genetic Predisposition to Disease

Share to Lung Neoplasms

Share to MicroRNAs

Share to Models, Genetic

Source

Identifiers

PMID: 26004789
DOI: 10.1142/S0219720015500146

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identifying human microRNA-disease associations by a new diffusion-based method.PMID 26004789Read ↗

DF-MDA: An effective diffusion-based computational model for predicting miRNA-disease association.Semantic proximity Read ↗

Similarity-based methods for potential human microRNA-disease association prediction.Semantic proximity Read ↗

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

PMDAGS: Predicting miRNA-Disease Associations With Graph Nonlinear Diffusion Convolution Network and Similarities.Semantic proximity Read ↗

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

Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA-Disease Association.Semantic proximity Read ↗

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

A Framework for Integrating Multiple Biological Networks to Predict MicroRNA-Disease Associations.Semantic proximity Read ↗

Integrative approaches for predicting microRNA function and prioritizing disease-related microRNA using biological interaction networks.Semantic proximity Read ↗

Predicting MicroRNA-Disease Associations Based on Improved MicroRNA and Disease Similarities.Semantic proximity Read ↗

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

Prediction of MicroRNA-Disease Potential Association Based on Sparse Learning and Multilayer Random Walks.Semantic proximity Read ↗

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