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MicroRNAs

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Role of Machine Learning in Liquid Biopsy of Brain Tumours.

JPMA. The Journal of the Pakistan Medical Association
Liquid biopsy has multiple benefits and is used extensively in other fields of oncology, but its role in neuro-oncology has been limited so far. Multiple tumour-derived materials like circulating tumour cells (CTCs), tumour-educated platelets (TEPs),...

Advances in applications of artificial intelligence algorithms for cancer-related miRNA research.

Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences
MiRNAs are a class of small non-coding RNAs, which regulate gene expression post-transcriptionally by partial complementary base pairing. Aberrant miRNA expressions have been reported in tumor tissues and peripheral blood of cancer patients. In recen...

Parkinson's Disease Diagnosis Using miRNA Biomarkers and Deep Learning.

Frontiers in bioscience (Landmark edition)
BACKGROUND: The current standard for Parkinson's disease (PD) diagnosis is often imprecise and expensive. However, the dysregulation patterns of microRNA (miRNA) hold potential as a reliable and effective non-invasive diagnosis of PD.

BioKA: a curated and integrated biomarker knowledgebase for animals.

Nucleic acids research
Biomarkers play an important role in various area such as personalized medicine, drug development, clinical care, and molecule breeding. However, existing animals' biomarker resources predominantly focus on human diseases, leaving a significant gap i...

DiMo: discovery of microRNA motifs using deep learning and motif embedding.

Briefings in bioinformatics
MicroRNAs are small regulatory RNAs that decrease gene expression after transcription in various biological disciplines. In bioinformatics, identifying microRNAs and predicting their functionalities is critical. Finding motifs is one of the most well...

miWords: transformer-based composite deep learning for highly accurate discovery of pre-miRNA regions across plant genomes.

Briefings in bioinformatics
Discovering pre-microRNAs (miRNAs) is the core of miRNA discovery. Using traditional sequence/structural features, many tools have been published to discover miRNAs. However, in practical applications like genomic annotations, their actual performanc...

MSGCL: inferring miRNA-disease associations based on multi-view self-supervised graph structure contrastive learning.

Briefings in bioinformatics
Potential miRNA-disease associations (MDA) play an important role in the discovery of complex human disease etiology. Therefore, MDA prediction is an attractive research topic in the field of biomedical machine learning. Recently, several models have...

An efficient deep learning based predictor for identifying miRNA-triggered phasiRNA loci in plant.

Mathematical biosciences and engineering : MBE
Phasic small interfering RNAs are plant secondary small interference RNAs that typically generated by the convergence of miRNAs and polyadenylated mRNAs. A growing number of studies have shown that miRNA-initiated phasiRNA plays crucial roles in regu...

Extraction of microRNA-target interaction sentences from biomedical literature by deep learning approach.

Briefings in bioinformatics
MicroRNA (miRNA)-target interaction (MTI) plays a substantial role in various cell activities, molecular regulations and physiological processes. Published biomedical literature is the carrier of high-confidence MTI knowledge. However, digging out th...

Machine learning on thyroid disease: a review.

Frontiers in bioscience (Landmark edition)
This study reviews the recent progress of machine learning for the early diagnosis of thyroid disease. Based on the results of this review, different machine learning methods would be appropriate for different types of data for the early diagnosis of...