Technology in cancer research & treatment
39703069
Clear cell renal cell carcinoma (ccRCC) is a highly lethal urinary malignancy with poor overall survival (OS) rates. Integrating computer vision and machine learning in pathomics analysis offers potential for enhancing classification, prognosis, and ...
Proteins associated with multiple diseases often interact, forming disease modules that are critical for understanding disease mechanisms. This study integrates protein-protein interactions (PPIs) and Gene Ontology data using non-negative matrix fact...
Machine learning has emerged as a transformative tool for elucidating cellular heterogeneity in single-cell RNA sequencing. However, a significant challenge lies in the "black box" nature of deep learning models, which obscures the decision-making pr...
PURPOSE: Mitochondria are involved in septic shock and inflammatory response syndrome, which severely affects the life security of patients. It is necessary to recognize and explore the immune-mitochondrial genes in septic shock.
Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples. Tradi...
Aortic dissection (AD) is one of the most dangerous diseases of the cardiovascular system, which is characterized by acute onset and poor prognosis, while the pathogenesis of AD is still unclear and may affect or even delay the diagnosis of AD. Ancho...
BACKGROUND: Juvenile idiopathic arthritis (JIA), superseding juvenile rheumatoid arthritis (JRA), is a chronic autoimmune disease affecting children and characterized by various types of childhood arthritis. JIA manifests clinically with joint inflam...
BACKGROUND: Chicken embryos emerge from their shell by the piercing movement of the hatching muscle. Although considered a key player during hatching, with activity that imposes a substantial metabolic demand, data are still limited. The study provid...
The Homo sapiens Chromosomal Location Ontology (HSCLO) is designed to facilitate the integration of human genomic features into biomedical knowledge graphs from releases GRCh37 and GRCh38 at multiple resolutions. HSCLO comprises two distinct versions...
Classical genomic prediction approaches rely on statistical associations between traits and markers rather than their biological significance. Biologically informed selection of genomic regions can help prioritize polymorphisms by considering underly...