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

In silico prediction of potential miRNA-disease association using an integrative bioinformatics approach based on kernel fusion.

Journal of cellular and molecular medicine - 1 Jan 2020

Guan Na-Na, Wang Chun-Chun, Zhang Li, Huang Li, Li Jian-Qiang, Piao Xue

Abstract excerpt

Accumulating experimental evidence has demonstrated that microRNAs (miRNAs) have a huge impact on numerous critical biological processes and they are associated with different complex human diseases. Nevertheless, the task to predict potential miRNAs related to diseases remains difficult. In this paper, we developed a Kernel Fusion-based Regularized Least Squares for MiRNA-Disease Association prediction model...

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

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Computer Simulation

Share to Genetic Association Studies

Share to Genetic Predisposition to Disease

Share to MicroRNAs

Share to Neoplasms

Source

Open in PubMed Open full text

Identifiers

PMID: 31747722
DOI: 10.1111/jcmm.14765
PMCID: PMC6933403

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

In silico prediction of potential miRNA-disease association using an integrative bioinformatics approach based on kernel fusion.PMID 31747722Read ↗

MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA-disease association prediction.Semantic proximity Read ↗

A Method Based On Dual-Network Information Fusion to Predict MiRNA-Disease Associations.Semantic proximity Read ↗

FKL-Spa-LapRLS: an accurate method for identifying human microRNA-disease associationSemantic proximity Read ↗

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

MDSCMF: Matrix Decomposition and Similarity-Constrained Matrix Factorization 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 ↗

GIMDA: Graphlet interaction-based MiRNA-disease association prediction.Semantic proximity Read ↗

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

Prediction of Potential MicroRNA-Disease Association Using Kernelized Bayesian Matrix Factorization.Semantic proximity Read ↗

An improved random forest-based computational model for predicting novel miRNA-disease associations.Semantic proximity Read ↗

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

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

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