Identification of virulence factors (VFs) is critical for expanding our knowledge on bacterial pathogenesis and also for developing targeted strategies for the prevention and treatment of related infectious diseases. Understanding virulence factors r...
Accurate skin lesion segmentation is critical for improving early diagnosis of skin cancer. In this study, we propose AttenUNeT X, a novel extension of the U-Net architecture that integrates three key enhancements: (i) a feedback mechanism within dec...
BACKGROUND: Accurate multicancer classification constitutes a cornerstone of modern oncology, offering critical insights into diagnosis, therapeutic decision-making, and prognostication. Numerous existing approaches, however, remain restricted to lim...
BACKGROUND: RNA methylation (RM) regulates gene expression regulation, RNA stability, and protein translation. Accurate prediction of RM modification sites is essential for understanding their biological functions. However, existing wet-lab detection...
Predicting protein‒protein interactions (PPIs) plays a crucial role in understanding biological processes. Although biological experimental methods can identify PPIs, they are costly, time-consuming, labor-intensive, and often lack stability. In cont...
BACKGROUND: Single-cell RNA sequencing (scRNA-seq) provides extensive opportunities to explore cellular heterogeneity but is often limited by substantial technical noise and variability. The prevalence of zero counts, arising from both biological var...
. Magnetic particle imaging (MPI) is an emerging imaging technique based on superparamagnetic iron oxide nanoparticles, offering high sensitivity and rapid imaging. However, in measurement-based MPI, image quality is degraded by noise arising during ...
Journal of chemical information and modeling
Nov 18, 2025
Chemical allergens are prevalent in both consumer and industrial products, often triggering hypersensitivity reactions with significant public health and regulatory implications. Traditional experimental screening is time-consuming and labor-intensiv...
OBJECTIVE: To evaluate the feasibility of using contrast enhancement boost (CE-Boost) combined with super-resolution deep learning reconstruction (SR-DLR) to reduce contrast agent dosage in pediatric patients with congenital heart disease (CHD).
Model-informed drug development (MIDD) plays an important role in pharmacometrics by leveraging mathematical models to optimize drug dosing strategies. Traditional methods such as nonlinear mixed effects modeling (NONMEM) have long been the gold stan...
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