LLCMDA: A Novel Method for Predicting miRNA Gene and Disease Relationship Based on Locality-Constrained Linear Coding-Reference-Cited by-同舟云学术

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LLCMDA: A Novel Method for Predicting miRNA Gene and Disease Relationship Based on Locality-Constrained Linear Coding

Published:2018-11-28 Issue: Volume:9 Page:
ISSN:1664-8021
Container-title:Frontiers in Genetics
language:
Short-container-title:Front. Genet.

Author:

Qu Yu,Zhang Huaxiang,Lyu Chen,Liang Cheng

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Publisher

Frontiers Media SA

Subject

Genetics(clinical),Genetics,Molecular Medicine

Reference56 articles.

1. The functions of animal microRNAs;Ambros;Nature,2004

2. DRMDA: deep representations-based miRNA-disease association prediction;Chen;J. Cell. Mol. Med.

3. EGBMMDA: extreme gradient boosting machine for MiRNA-disease association prediction;Chen;Cell Death Dis.

4. RWRMDA: predicting novel human microRNA-disease associations;Chen;Mol. Biosyst.,2012

5. MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA-disease association prediction;Chen;J. Transl. Med.

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1. An efficient model for predicting human diseases through miRNA based on multiple-types of contrastive learning;Frontiers in Microbiology;2023-12-14

2. Identification of Disease-Associated MicroRNAs Via Locality-Constrained Linear Coding-Based Ensemble Learning;Journal of Computational Biology;2023-08-01

3. Prediction Models Based On miRNA-Disease Relationship: Diagnostic Relevance To Multiple Diseases including COVID-19;Current Pharmaceutical Biotechnology;2023-08

4. MSGCL: inferring miRNA–disease associations based on multi-view self-supervised graph structure contrastive learning;Briefings in Bioinformatics;2023-02-15

5. MGCNRF: Prediction of Disease-Related miRNAs Based on Multiple Graph Convolutional Networks and Random Forest;IEEE Transactions on Neural Networks and Learning Systems;2023

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