Genetics

scAClc: A Multi-Objective Adaptive Clustering Framework for Single-Cell Transcriptomics via Contrastive and Resolution-Aware Representation Learning.

Single-cell RNA sequencing (scRNA-seq) enables whole-transcriptomic profiling at single-cell resolut...

Integrating metagenomics into legume breeding: A breeder-centered roadmap from core microbiomes to precision inoculation.

Metagenomics, culture-independent profiling of genetic material recovered from environmental samples...

HeFS: Helper-Enhanced Feature Selection via Pareto-Optimized Genetic Search.

INTRODUCTION: Feature selection plays a crucial role in improving predictive performance and interpr...

Investigating the potential risk of nicotine exposure on glioblastoma: Integrating Mendelian randomization and network toxicology analysis.

OBJECTIVE: To investigate the potential risk of nicotine exposure on glioblastoma multiforme (GBM). ...

Mechanistic Design of Graphdiyne-Based Multimodal Sensing Integrating Machine Learning and Photothermal Dynamics for Precision Recognition and On-Demand Inactivation.

Rapid and accurate detection of pathogenic bacteria remains essential for infection control and time...

Evaluating Public Sentiment on Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Compared With Other Mental Health Disorders From Posts on X (Formerly Known as Twitter): Longitudinal Analysis.

BACKGROUND: Neurodevelopmental disorders, especially attention-deficit/hyperactivity disorder (ADHD)...

Improved tumor-only variant calling and mutation burden estimation with VarNet-T.

Somatic variant calling algorithms typically detect mutations in cancer genomes by comparing sequenc...

Volatomics-based biomarkers for non-invasive diagnosis and monitoring of inflammatory bowel disease.

BACKGROUND: Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is a...

Predicting mild familial exudative vitreoretinopathy with autosomal dominant inheritance using deep learning.

Oxide interface-based polymorphic electronic devices for neuromorphic computing.

Aside from recent advances in artificial intelligence (AI) models, specialized AI hardware is crucia...

Integrative analysis of single-cell and bulk RNA sequencing data using machine learning identifies PTGDS as a key subsynovial fibroblast gene in osteoarthritis.

Multi-omics and AI-guided discovery and validation of sisomicin as a COPA-targeting agent for pathological scar inhibition.

BACKGROUND: Pathological scars, including hypertrophic scars and keloids, are fibrotic skin disorder...

Machine learning-based programmed cell death gene signature for prognosis and drug sensitivity in breast cancer.

Breast cancer (BRCA) heterogeneity necessitates robust prognostic biomarkers. Programmed cell death ...

Simulation-based inference captures non-Markovian effects as exemplified in protein production kinetics through cell division.

Inferring protein production kinetics in dividing cells is complicated by protein inheritance from t...

ACAT1-mediated lactylation reprogramming governs immune-stromal crosstalk in ulcerative colitis.

Ulcerative colitis (UC), a chronic inflammatory bowel disorder characterized by progressive colonic ...

Linking rare variants to cell-type function in profound autism with brain transcriptomics and foundation models.

Genetic association studies have identified numerous genes harboring protein-disrupting variants in ...

"Unpatients" in haemostasis and thrombosis. A yardstick of current paths in healthy carriers of a genetic susceptibility.

"Unpatients" are health-conscious individuals -carrying a genetic susceptibility whose impact is unc...

Predicting dairy cattle PL via longitudinal rumen microbiome dynamics using machine learning approaches.

Aging is a spontaneous biological process involving intricate regulatory mechanisms over time. Studi...

Radiopathomic Graph Deep Learning for Multiscale Spatial-Contextual Modeling of Intratumoral Heterogeneity to Predict Breast Cancer Response to Neoadjuvant Therapy.

Purpose To develop an explainable radio-pathomic graph deep-learning (RPGDL) system for multiscale s...

Integrated multi-omics and experimental validation for identifying novel biomarkers of acute myocardial infarction.

Acute myocardial infarction (AMI) remains a leading cause of morbidity and mortality, and early diag...

Multiomics and deep learning dissect regulatory syntax in human development.

Transcription factors establish cell identity during development by binding regulatory DNA in a sequ...