DNRLCNN: A CNN Framework for Identifying MiRNA-Disease Associations Using Latent Feature Matrix Extraction with Positive Samples.
Sign Up to like & getrecommendations! Published in 2022 at "Interdisciplinary sciences, computational life sciences"
DOI: 10.1007/s12539-022-00509-z
Abstract: Emerging evidence indicates that miRNAs have strong relationships with many human diseases. Investigating the associations will contribute to elucidating the activities of miRNAs and pathogenesis mechanisms, and providing new opportunities for disease diagnosis and drug… read more here.
Keywords: positive samples; latent feature; mirna disease; feature ... See more keywords
Predicting microRNA-disease associations using bipartite local models and hubness-aware regression
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DOI: 10.1080/15476286.2018.1517010
Abstract: ABSTRACT The development and progression of numerous complex human diseases have been confirmed to be associated with microRNAs (miRNAs) by various experimental and clinical studies. Predicting potential miRNA-disease associations can help us understand the underlying… read more here.
Keywords: disease associations; disease; model; bipartite local ... See more keywords
A graph auto-encoder model for miRNA-disease associations prediction
Sign Up to like & getrecommendations! Published in 2021 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbaa240
Abstract: Emerging evidence indicates that the abnormal expression of miRNAs involves in the evolution and progression of various human complex diseases. Identifying disease-related miRNAs as new biomarkers can promote the development of disease pathology and clinical… read more here.
Keywords: encoder; disease associations; disease; model ... See more keywords
MiRNA-disease association prediction based on meta-paths
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DOI: 10.1093/bib/bbab571
Abstract: Since miRNAs can participate in the posttranscriptional regulation of gene expression, they may provide ideas for the development of new drugs or become new biomarkers for drug targets or disease diagnosis. In this work, we… read more here.
Keywords: meta paths; association prediction; based meta; disease association ... See more keywords
Prediction of potential miRNA-disease associations based on stacked autoencoder
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DOI: 10.1093/bib/bbac021
Abstract: In recent years, increasing biological experiments and scientific studies have demonstrated that microRNA (miRNA) plays an important role in the development of human complex diseases. Therefore, discovering miRNA-disease associations can contribute to accurate diagnosis and… read more here.
Keywords: disease associations; mirna disease; potential mirna; disease ... See more keywords
Research progress of miRNA-disease association prediction and comparison of related algorithms
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DOI: 10.1093/bib/bbac066
Abstract: With an in-depth understanding of noncoding ribonucleic acid (RNA), many studies have shown that microRNA (miRNA) plays an important role in human diseases. Because traditional biological experiments are time-consuming and laborious, new calculation methods have… read more here.
Keywords: disease; disease association; mirna disease; association prediction ... See more keywords
MLRDFM: a multi-view Laplacian regularized DeepFM model for predicting miRNA-disease associations
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac079
Abstract: MOTIVATION MicroRNAs (miRNAs), as critical regulators, are involved in various fundamental and vital biological processes, and their abnormalities are closely related to human diseases. Predicting disease-related miRNAs is beneficial to uncovering new biomarkers for the… read more here.
Keywords: disease; deepfm; multi view; model ... See more keywords
Identification of miRNA-disease associations via deep forest ensemble learning based on autoencoder
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DOI: 10.1093/bib/bbac104
Abstract: Increasing evidences show that the occurrence of human complex diseases is closely related to microRNA (miRNA) variation and imbalance. For this reason, predicting disease-related miRNAs is essential for the diagnosis and treatment of complex human… read more here.
Keywords: via deep; disease; deep forest; disease associations ... See more keywords
idenMD-NRF: a ranking framework for miRNA-disease association identification
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DOI: 10.1093/bib/bbac224
Abstract: Identifying miRNA-disease associations is an important task for revealing pathogenic mechanism of complicated diseases. Different computational methods have been proposed. Although these methods obtained encouraging performance for detecting missing associations between known miRNAs and diseases,… read more here.
Keywords: association identification; disease association; mirna disease; idenmd nrf ... See more keywords
Predicting miRNA-disease associations based on graph attention networks and dual Laplacian regularized least squares
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DOI: 10.1093/bib/bbac292
Abstract: Increasing biomedical evidence has proved that the dysregulation of miRNAs is associated with human complex diseases. Identification of disease-related miRNAs is of great importance for disease prevention, diagnosis and remedy. To reduce the time and… read more here.
Keywords: disease; dual laplacian; disease associations; mirna disease ... See more keywords
SFGAE: a self-feature-based graph autoencoder model for miRNA-disease associations prediction
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DOI: 10.1093/bib/bbac340
Abstract: Increasing evidence has suggested that microRNAs (miRNAs) are important biomarkers of various diseases. Numerous graph neural network (GNN) models have been proposed for predicting miRNA-disease associations. However, the existing GNN-based methods have over-smoothing issue-the learned… read more here.
Keywords: disease; feature embeddings; self feature; disease associations ... See more keywords