Genetics

Deep learning detection of retinitis pigmentosa inheritance forms through synthetic data expansion of a rare disease dataset.

Artificial intelligence in microbiology: implications for metagenomics, diagnostics, and AMR surveillance.

Artificial intelligence (AI) is now a key player in modern microbiology, as it enables high-resolution analyses of genomic, metagenomic, and clinical data for the monitoring of infectious disease and antimicrobial resistance (AMR). Considerable advancements in deep learning, transformer-based sequence models, graph neural networks, and multimodal architectures have greatly improved microbial class...

High-throughput strategy for targeting MDM2 in uveal melanoma to reverse radiation therapy resistance.

Uveal melanoma (UM) presents a formidable clinical challenge due to its marked resistance to radiotherapy. In this study, an integrative strategy comb...

Coalescence and translation: A language model for population genetics.

Probabilistic models such as the sequentially Markovian coalescent have long provided a powerful framework for population genetic inference, enabling ...

Clinical relevance of the characterisation and quantification of CD8+ T-cell infiltration in high-grade serous ovarian carcinoma using machine learning-based image analysis of dual immunostaining.

INTRODUCTION: High-grade serous carcinoma (HGSC) is the most common and aggressive subtype of ovarian cancer. Although tumour stage and complete cytor...

Deep learning on genome-wide association studies to predict the patient-specific risk of radiation-induced erectile dysfunction.

OBJECTIVE: Radiation-induced erectile dysfunction (RIED) is a frequent, unpredictable complication following radiotherapy for prostate cancer. We hypo...

Genomic Determinants of Response to Alpelisib Plus Fulvestrant in the SOLAR-1 Trial.

BACKGROUND: Approximately 40% of patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-), advanced br...

Identifying mitochondria-related signatures for tuberculosis diagnosis through machine learning on single-cell transcriptomics data and experimental verification.

Tuberculosis (TB) remains a major cause of infectious disease mortality. Early diagnosis is crucial for curbing transmission and initiating timely tre...

Accelerated long-read variant calling with Clair3 for whole-genome sequencing.

SUMMARY: The rapid growth of genomic data and increasing adoption of long-read sequencing technologies have rendered variant calling one of the most c...

Regulatory B cells and SIVA1-LAG3 immune suppression predict poor prognosis in prostate cancer.

Prostate cancer (PCa) is among the most prevalent malignancies affecting men globally. The immunosuppressive characteristics of the tumor microenviron...

The emergence of superficial dermatophytosis due to Trichophyton indotineae and Trichophyton mentagrophytes genotypes VII and II* in New York: a need for comprehensive testing approaches.

We report a rapid increase in dermatophyte infections in New York City and surrounding counties from 2022 to 2024. Reported cases include 135 of Trich...

Differentiating long QT syndrome genotypes using electrocardiographic geometric parameterization and machine learning approaches.

Long QT Syndrome (LQTS) is an inherited cardiac disorder characterized by dysfunctional cardiac ion channels, which result in prolonged QT intervals o...

Predictive bioactivity modeling and structural binding analysis for the identification of potential SMYD3 modulators.

SMYD3 is a lysine methyltransferase involved in epigenetic regulation and oncogenic transcription, making it an attractive yet challenging therapeutic...

Deep Learning-Enabled Multimodal AFM Image Enhancement: Correlation Analysis between Surface Topography and Multiphysics Fields.

In materials science, performing a synchronous correlative analysis of multiphysics fields at the nanoscale is critical for advancements in material c...

Multigated DNA Cascade Amplifier for Ultrasensitive Spatiotemporal Imaging of PLS3 mRNA at the Single-Cell Level for Early Detection of Breast Cancer Metastasis.

Early detection of small metastatic foci is crucial for improving breast cancer patient survival. Plastin-3 (PLS3) has emerged as a key biomarker in b...

Tripleknock: predicting lethal effect of three-gene knockout in bacteria by deep learning.

Investigating the lethal effect of multi-gene knockout is essential for discovering novel antibiotic targets and metabolic engineering. Unlike single ...

Enhanced Quantitative Phosphocreatine MR Imaging of Skeletal Muscle Using a Global-Local Two-Branch Deep Learning Model.

PURPOSE: Phosphocreatine (PCr) is an essential marker of muscle metabolism, and accurate quantification of its (fs) and its exchange rate (ksw) is ess...

Integrative bioinformatics and machine learning identify shared molecular mechanisms and diagnostic biomarkers between Helicobacter pylori infection and atrial fibrillation.

BACKGROUND: Helicobacter pylori (H. pylori) infection and atrial fibrillation(AF) are major global health concerns. Emerging evidence has suggested a ...

Smart diagnostics: Leveraging artificial intelligence for accurate at-home COVID-19 testing.

Reverse transcriptase polymerase chain reaction (RT-PCR), the reference standard for COVID-19 diagnosis, is time-consuming, resource-intensive, and co...

Predicting sediment ecological state from metagenomes shows equal performance for taxonomic and functional features.

The use of environmental microbial DNA to monitor the ecological state in seafloor sediments has many advantages and efforts are being made to find re...