Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Digital telomere measurement by long-read sequencing distinguishes healthy aging from disease.

Telomere length is an important biomarker of organismal aging and cellular replicative potential, bu...

A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria.

Microorganisms, crucial for environmental equilibrium, could be destructive, resulting in detrimenta...

Improving platelet-RNA-based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification.

Liquid biopsy demonstrates excellent potential in patient management by providing a minimally invasi...

Dynamic Addressing Molecular Robot (DAMR): An Effective and Efficient Trial-and-Error Approach for the Analysis of Single Nucleotide Polymorphisms.

Accurate and efficient molecular recognition plays a crucial role in the fields of molecular detecti...

A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning.

Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects ...

Machine Learning-Assisted Direct RNA Sequencing with Epigenetic RNA Modification Detection via Quantum Tunneling.

RNA sequence information holds immense potential as a drug target for diagnosing various RNA-mediate...

Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment.

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate ...

Big data and deep learning for RNA biology.

The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (...

Artificial INtelligence to Support Informed DEcision-making (INSIDE) for Improved Literature Analysis in Oncology.

BACKGROUND: Defining optimal therapeutic sequencing strategies in prostate cancer (PC) is challengin...

Dual-extraction modeling: A multi-modal deep-learning architecture for phenotypic prediction and functional gene mining of complex traits.

Despite considerable advances in extracting crucial insights from bio-omics data to unravel the intr...

IPF-related new macrophage subpopulations and diagnostic biomarker identification - combine machine learning with single-cell analysis.

Idiopathic pulmonary fibrosis (IPF) is a chronic disease of unknown etiology that lacks a specific t...

The Prediction of Recombination Hotspot Based on Automated Machine Learning.

Meiotic recombination plays a pivotal role in genetic evolution. Genetic variation induced by recomb...

Artificial intelligence enables unified analysis of historical and landscape influences on genetic diversity.

While genetic variation in any species is potentially shaped by a range of processes, phylogeography...

DCRELM: dual correlation reduction network-based extreme learning machine for single-cell RNA-seq data clustering.

Single-cell ribonucleic acid sequencing (scRNA-seq) is a high-throughput genomic technique that is u...

Effective training of nanopore callers for epigenetic marks with limited labelled data.

Nanopore sequencing platforms combined with supervised machine learning (ML) have been effective at ...

Machine learning algorithms integrate bulk and single-cell RNA data to unveil oxidative stress following intracerebral hemorrhage.

BACKGROUND: Increased oxidative stress (OS) activity following intracerebral hemorrhage (ICH) had si...

Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.

Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk f...

A Systematic Review of Genetics- and Molecular-Pathway-Based Machine Learning Models for Neurological Disorder Diagnosis.

The process of identification and management of neurological disorder conditions faces challenges, p...

Machine learning integrative approaches to advance computational immunology.

The study of immunology, traditionally reliant on proteomics to evaluate individual immune cells, ha...

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