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MicroRNAs

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Exploring the Study of miR-1301 Inhibiting the Proliferation and Migration of Squamous Cell Carcinoma YD-38 Cells through PI3K/AKT Pathway under Deep Learning Medical Images.

Computational intelligence and neuroscience
With the rapid development and application of deep learning medical image recognition, natural language processing, and other fields, at the same time, deep learning has become the most popular research direction in the field of image processing and ...

AIME: Autoencoder-based integrative multi-omics data embedding that allows for confounder adjustments.

PLoS computational biology
In the integrative analyses of omics data, it is often of interest to extract data representation from one data type that best reflect its relations with another data type. This task is traditionally fulfilled by linear methods such as canonical corr...

Predicting miRNA-Disease Association Based on Neural Inductive Matrix Completion with Graph Autoencoders and Self-Attention Mechanism.

Biomolecules
Many studies have clarified that microRNAs (miRNAs) are associated with many human diseases. Therefore, it is essential to predict potential miRNA-disease associations for disease pathogenesis and treatment. Numerous machine learning and deep learnin...

Hybrid Deep Neural Network for Handling Data Imbalance in Precursor MicroRNA.

Frontiers in public health
Over the last decade, the field of bioinformatics has been increasing rapidly. Robust bioinformatics tools are going to play a vital role in future progress. Scientists working in the field of bioinformatics conduct a large number of researches to ex...

Biological features between miRNAs and their targets are unveiled from deep learning models.

Scientific reports
MicroRNAs (miRNAs) are ~ 22 nucleotide ubiquitous gene regulators. They modulate a broad range of essential cellular processes linked to human health and diseases. Consequently, identifying miRNA targets and understanding how they function are critic...

GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder.

PLoS computational biology
microRNAs (miRNAs) are small non-coding RNAs related to a number of complicated biological processes. A growing body of studies have suggested that miRNAs are closely associated with many human diseases. It is meaningful to consider disease-related m...

Combination of artificial intelligence-based endoscopy and miR148a methylation for gastric indefinite dysplasia diagnosis.

Journal of clinical laboratory analysis
BACKGROUND AND AIM: Gastrointestinal endoscopy and biopsy-based pathological findings are needed to diagnose early gastric cancer. However, the information of biopsy specimen is limited because of the topical procedure; therefore, pathology doctors s...

Discriminating Neoplastic from Nonneoplastic Tissues Using an miRNA-Based Deep Cancer Classifier.

The American journal of pathology
Next-generation sequencing has enabled the collection of large biological data sets, allowing novel molecular-based classification methods to be developed for increased understanding of disease. miRNAs are small regulatory RNA molecules that can be q...