AIMC Topic: MicroRNAs
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[Moving towards a personalized oncology: The contribution of genomic techniques and artificial intelligence in the use of circulating tumor biomarkers].
Bulletin du cancer
Jan 13, 2022
Technological advances, in particular the development of high-throughput sequencing, have led to the emergence of a new generation of molecular biomarkers for tumors. These new tools have profoundly changed therapeutic management in oncology, with in...
Predicting miRNA-Disease Association Based on Neural Inductive Matrix Completion with Graph Autoencoders and Self-Attention Mechanism.
Biomolecules
Jan 2, 2022
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
Dec 23, 2021
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
Dec 10, 2021
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
Dec 10, 2021
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...
Systems biology and machine learning approaches identify drug targets in diabetic nephropathy.
Scientific reports
Dec 6, 2021
Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the underlying mechanisms have not yet been comprehensively understood. In this study, a systematic appr...
Drug Design
Gene Expression Profiling
Gene Regulatory Networks
Mice
Animals
Male
Global Health
Signal Transduction
Support Vector Machine
Cluster Analysis
MicroRNAs
Diabetic Nephropathies
Computational Biology
Systems Biology
Epigenesis, Genetic
Humans
Machine Learning
Algorithms
Chemistry, Pharmaceutical
Kidney Cortex
Microarray Analysis
Regression Analysis
Kidney Medulla
Oligonucleotide Array Sequence Analysis
Principal Component Analysis
Mice, Inbred DBA
Linear Models
Combination of artificial intelligence-based endoscopy and miR148a methylation for gastric indefinite dysplasia diagnosis.
Journal of clinical laboratory analysis
Nov 22, 2021
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
Nov 10, 2021
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...
Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows.
STAR protocols
Oct 23, 2021
MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a mach...
miRbiom: Machine-learning on Bayesian causal nets of RBP-miRNA interactions successfully predicts miRNA profiles.
PloS one
Oct 12, 2021
Formation of mature miRNAs and their expression is a highly controlled process. It is very much dependent upon the post-transcriptional regulatory events. Recent findings suggest that several RNA binding proteins beyond Drosha/Dicer are involved in t...
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