ANMDA: anti-noise based computational model for predicting potential miRNA-disease associations

ANMDA: anti-noise based computational model for predicting potential miRNA-disease associations

Background: A growing proportion of research has proved that microRNAs (miRNAs) can regulate the function of target genes and have close relations with various diseases. Developing computational methods to exploit more potential miRNA-disease associations can provide clues for further functional res...

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Bibliographic Details
Main Authors: Chen, X.-J (Author), Hua, X.-Y (Author), Jiang, Z.-R (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
Anti noise algorithms
Area Under Curve
area under the curve
biology
Computational Biology
Computational methods
Computational model
Database versions
Disease associations
Forecasting
genetic predisposition
Genetic Predisposition to Disease
human
Humans
k-means
K-means clustering
Light gradient boosting machine
metabolism
microRNA
MicroRNAs
miRNA-disease association
Negative examples
Noise smoothing
Prediction performance
receiver operating characteristic
Receiver operating characteristic curves
RNA
ROC Curve
Sampling with replacement
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