Single-molecule detection (SMD) holds considerable promise in biomedical research. Although atomic force microscopy (AFM) provides an important technique with nanoscale resolution for SMD, its broader application is limited by labeling challenges and...
Journal of computer-aided molecular design
Dec 24, 2025
In recent decades, the rapid pace of digital transformation marks a transformative era for the healthcare and pharmaceutical industries. The incorporation of innovative technology, specifically Artificial Intelligence (AI) and its derivatives, has dr...
BACKGROUND: The P53-mutated Hepatocellular Carcinoma (HCC) is an aggressive variant associated with vascular endothelial growth factor (VEGF) overexpression and increased microvascular density. This study aimed to develop an MRI-based deep learning m...
In the event of a large-scale radiological or nuclear emergency, a rapid, high-throughput screening tool will be essential for efficient triage of potentially exposed individuals, optimizing scarce medical resources and ensuring timely care. The obje...
High-throughput screening for inhibitors of protein-protein interactions (PPIs) provides vital information for therapeutic intervention in diseases driven by aberrant PPIs. Traditionally, the discovery of PPI inhibitors involves sequential steps: in ...
OBJECTIVE: To create an automated PET/CT segmentation method and radiomics model to forecast Mismatch repair (MMR) and TP53 gene expression in endometrial cancer patients, and to examine the effect of gene expression variability on image texture feat...
International journal of molecular sciences
May 24, 2025
Traumatic brain injury (TBI) triggers a cascade of molecular and cellular disturbances, including apoptosis, inflammation, and destabilization of neuronal connections. The transcription factor p53 plays a pivotal role in regulating cell fate followin...
PURPOSE: This study was designed to construct progressive binary classification models based on radiomics and deep learning to predict the presence of epidermal growth factor receptor ( EGFR ) and TP53 mutations and to assess the models' capacities t...
BACKGROUND: Advancements in the management of gastric cancer (GC) and innovative therapeutic approaches highlight the significance of the role of biomarkers in GC prognosis. Machine-learning (ML)-based methods can be applied to identify the most impo...
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