Genetics

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

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Ensemble-learning approach improves fracture prediction using genomic and phenotypic data.

UNLABELLED: This study presents an innovative ensemble machine learning model integrating genomic an...

Interpretable Multimodal Fusion Model for Bridged Histology and Genomics Survival Prediction in Pan-Cancer.

Understanding the prognosis of cancer patients is crucial for enabling precise diagnosis and treatme...

Development of a MVI associated HCC prognostic model through single cell transcriptomic analysis and 101 machine learning algorithms.

Hepatocellular carcinoma (HCC) is an exceedingly aggressive form of cancer that often carries a poor...

Screening and validating genes associated with cuproptosis in systemic lupus erythematosus by expression profiling combined with machine learning.

Cell death has long been a focal point in life sciences research, and recently, scientists have disc...

A deep-learning model for quantifying circulating tumour DNA from the density distribution of DNA-fragment lengths.

The quantification of circulating tumour DNA (ctDNA) in blood enables non-invasive surveillance of c...

Machine-learning assisted discovery unveils novel interplay between gut microbiota and host metabolic disturbance in diabetic kidney disease.

Diabetic kidney disease (DKD) is a serious healthcare dilemma. Nonetheless, the interplay between th...

DHUpredET: A comparative computational approach for identification of dihydrouridine modification sites in RNA sequence.

Laboratory-based detection of D sites is laborious and expensive. In this study, we developed effect...

Leveraging Automated Machine Learning for Environmental Data-Driven Genetic Analysis and Genomic Prediction in Maize Hybrids.

Genotype, environment, and genotype-by-environment (G×E) interactions play a critical role in shapin...

EVlncRNA-net: A dual-channel deep learning approach for accurate prediction of experimentally validated lncRNAs.

Long non-coding RNAs (lncRNAs) play key roles in numerous biological processes and are associated wi...

TARSL: Triple-Attention Cross-Network Representation Learning to Predict Synthetic Lethality for Anti-Cancer Drug Discovery.

Cancer is a multifaceted disease that results from co-mutations of multi biological molecules. A pro...

Deep mutational learning for the selection of therapeutic antibodies resistant to the evolution of Omicron variants of SARS-CoV-2.

Most antibodies for treating COVID-19 rely on binding the receptor-binding domain (RBD) of SARS-CoV-...

scHeteroNet: A Heterophily-Aware Graph Neural Network for Accurate Cell Type Annotation and Novel Cell Detection.

Single-cell RNA sequencing (scRNA-seq) has unveiled extensive cellular heterogeneity, yet precise ce...

A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors.

BACKGROUND: Major depressive disorder (MDD) is among the leading causes of disability worldwide and ...

Deep Learning Enhanced Near Infrared-II Imaging and Image-Guided Small Interfering Ribonucleic Acid Therapy of Ischemic Stroke.

Small interfering RNA (siRNA) targeting the NOD-like receptor family pyrin domain-containing 3 (NLRP...

Investigation of cell development and tissue structure network based on natural Language processing of scRNA-seq data.

BACKGROUND: Single-cell multi-omics technologies, particularly single-cell RNA sequencing (scRNA-seq...

Development of a microRNA-Based age estimation model using whole-blood microRNA expression profiling.

Age estimation is a critical aspect of human identification. Traditional methods, reliant on morphol...

Machine Learning-Aided Identification of Fecal Extracellular Vesicle microRNA Signatures for Noninvasive Detection of Colorectal Cancer.

Colorectal cancer (CRC) remains a formidable threat to human health, with considerable challenges pe...

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