Article

GNMFLMI: Graph Regularized Nonnegative Matrix Factorization for Predicting LncRNA-MiRNA Interactions

2019-11-09

Abstract excerpt

Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been involved in various biological processes. Emerging evidence suggests that the interactions between lncRNAs and miRNAs play an important role in regulating of genes and the development of many diseases. Due to the limited scale of known lncRNA-miRNA interactions, and expensive time and labor costs for identifying them by biological experiments, more ac...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 1eaff558-869d-52cf-9825-206fd76b2e8a
DOI: 10.1101/835934

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

GNMFLMI: Graph Regularized Nonnegative Matrix Factorization for Predicting LncRNA-MiRNA InteractionsDOI 10.1101/835934Read

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

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

SNMFSMMA: using symmetric nonnegative matrix factorization and Kronecker regularized least squares to predict potential small molecule-microRNA association.Semantic proximity Read

Dual-Network Collaborative Matrix Factorization for predicting small molecule-miRNA associations.Semantic proximity Read

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

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

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

Bipartite graph-based collaborative matrix factorization method for predicting miRNA-disease associations.Semantic proximity Read

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

ILDMSF: Inferring Associations Between Long Non-Coding RNA and Disease Based on Multi-Similarity FusionSemantic proximity Read

SPLHRNMTF: robust orthogonal non-negative matrix tri-factorization with self-paced learning and dual hypergraph regularization for predicting miRNA-disease associations.Semantic proximity Read

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