Genetics

Efficient evidence-based genome annotation with EviAnn.

Machine-learning-based ab initio gene finders have long been central to eukaryotic genome annotation, largely because gene expression data were historically expensive and limited. Modern sequencing technologies have transformed this landscape, making transcript evidence abundant and reliable, while proteins from many well-annotated genomes provide additional rich sources of evidence. Here we addre...

Multi-omics and metabolic flux modeling reveal that macrophage CYP27A1-derived 26-hydroxycholesterol drives immunosuppression and cancer malignancy.

Emerging evidence indicates that aberrant cholesterol metabolism in macrophages plays a role in tumorigenesis, however, how specific metabolites released by macrophages influence immunosurveillance and along with their potential as therapeutic targets and prognostic biomarkers, remain unclear. We integrated 465 single-cell multi-omics and 1,318 bulk RNA-seq samples of colorectal cancer (CRC) using...

A predictive model for pathological complete response in neoadjuvant-treated breast cancer: integrating pretreatment clinicopathologic and contrast-enhanced ultrasound characteristics via interpretable machine learning.

BACKGROUND: The ability to predict pathological complete response (pCR) prior to neoadjuvant therapy (NAT) would inform and facilitate tailored therap...

Preoperative Serum Alkaline Phosphatase Predicts Arteriovenous Fistula Maturation Failure.

INTRODUCTION: Arteriovenous fistula (AVF) maturation failure remains a major obstacle for hemodialysis, yet its underlying molecular drivers are poorl...

Generalizable Protein Folding Pathway Exploration with DA2-GRASP: Extending Beyond Miniproteins.

Elucidating protein dynamics is crucial for deciphering fundamental biological processes, from enzyme catalysis to cellular signaling, as its dysregul...

Routine biomarkers map response probability in HER2-positive breast cancer treated with neoadjuvant chemotherapy and dual HER2 blockade.

BACKGROUND: Pathologic complete response (pCR) after neoadjuvant chemotherapy and dual HER2 blockade is associated with improved outcomes in HER2-posi...

AI-driven Approach to Treat Acute Coronary Syndrome: A Review on Integration of AlphaFold in Cardiovascular Genomics.

INTRODUCTION: The constantly evolving nature of diseases has put humanity in a never- ending struggle for survival, adapting to each disease and fight...

Beyond the Classics: The Synergy of AI and Genomics Reveals an Expanded Repertoire of Pigmentation Genes.

Pigmentation has long served as a powerful system for exploring gene-trait relationships, yet much of the field has focused on a relatively narrow gro...

GenoEye: A machine learning-based framework for the prediction of intermediate eye color phenotypes.

Forensic DNA phenotyping (FDP) enables the prediction of externally visible characteristics from genetic data, providing valuable investigative leads....

Data-driven methods allow prediction of utility of DNA rework.

In forensic DNA casework, complex trace samples may benefit from rework procedures involving additional PCR replicates and lowered analytical threshol...

Forging New Pathways in Oncology: Strategic Insights from the 17th Annual Frontiers in Cancer Science Conference.

The 17th Annual Frontiers in Cancer Science (FCS) conference (2025) highlighted the convergence of multiomics, computational biology, and ancestry-spe...

Deep learning-enabled microfluidic digital PCR platform for efficient seven-color quantification.

Digital PCR (dPCR), as a high-sensitivity technology for absolute nucleic acid quantification, holds significant value in biomedical research and envi...

Nanopore sequencing with proteins: synchronization and dischronization of molecular dynamics simulations with laboratory and industrial developments.

Protein nanopores have revolutionized DNA sequencing by enabling long-read, real-time, and portable genomic analysis. This review traces the experimen...

Diagnostic challenges in re-emerging rickettsioses: why current tools fall short.

SUMMARYRickettsial diseases, encompassing scrub typhus, spotted fever group rickettsioses, and typhus group rickettsioses, represent a significant and...

An interpretable deep learning framework uncovers features governing CRISPR-Cas9 genome-editing efficiency.

MOTIVATION: CRISPR-Cas9 genome-editing efficiency is strongly influenced by the sequence composition and positional context of single-guide RNAs (sgRN...

Single-cell and machine learning-based neural regulation signature for prognosis prediction and immunotherapy response in lung adenocarcinoma.

OBJECTIVE: Lung adenocarcinoma (LUAD) molecular heterogeneity limits traditional prognostic models. Given the emerging role of neural regulation (NR) ...

An AI-driven deep learning pipeline for taxonomic classification and biodiversity assessment of deep-sea environmental DNA.

It is estimated that millions of species exist in the deep-sea environment, such as hydrothermal vents, cold seeps, abyssal plains and seamounts, whic...

A transparent and generalizable deep-learning framework for genomic ancestry prediction.

Accurately characterizing genetic ancestry is critical for ensuring reproducibility and fairness in genomic studies and downstream health research. Th...

Technology-driven revolution in CO2 fixation: From natural pathways to programmable Biosystems.

The escalating atmospheric CO2 concentration, exceeding 430 ppm since the pre-industrial era, presents a critical threat to global climate stability. ...

The Role of Intracellular ROS in the Development of Antimicrobial Resistance:A Convergent Mediator Linking Mutations and Horizontal Gene Transfer.

The development of antimicrobial resistance (AMR) is a major threat to global public health and environmental security. While antibiotics are known dr...