AIMC Topic: Gene Expression Profiling
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Interpretable graph Kolmogorov-Arnold networks for multi-cancer classification and biomarker identification using multi-omics data.
Scientific reports
Jul 29, 2025
The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational models in precision cancer diagnostics. This paper introduces Multi-Omics Graph Kolmogorov-Arnold Network...
SPP1 + macrophages facilitate pancreatic cancer progression via ITGB6-mediated interactions: evidence from integrated multi-omics analysis and experimental validation.
Immunologic research
Jul 28, 2025
Basement membranes (BMs) and tumor-associated macrophages (TAMs) are crucial stromal components in pancreatic cancer (PC), critically influencing disease progression. Bulk and single-cell RNA-seq (scRNA-seq) data were acquired from publicly available...
Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells.
European journal of medical research
Jul 24, 2025
BACKGROUND: Cardioembolic stroke (CS) and atherosclerosis (AS) are closely related diseases. Ferroptosis, a novel form of programmed cell death, may play a key role in CS and AS. However, the pathophysiological mechanisms underlying their coexistence...
Exploring the comorbidity mechanisms of ITGB2 in rheumatoid arthritis and membranous nephropathy through integrated bioinformatics analysis.
Renal failure
Jul 23, 2025
BACKGROUND: Patients with rheumatoid arthritis (RA) are more likely to comorbid renal diseases, with membranous nephropathy (MN) being the most common. This study aimed to explore the common pathogenesis between RA and MN using integrated bioinformat...
Histology image analysis of 13 healthy tissues reveals molecular-histological correlations.
Scientific reports
Jul 23, 2025
Gene expression is an important process in which genes guide the synthesis of proteins, and molecular-level differences often lead to individual phenotypic variations. Combining molecular information at the nano-level with phenotypic information at t...
An autoencoder learning method for predicting breast cancer subtypes.
PloS one
Jul 23, 2025
Heterogeneity of breast cancer poses several challenges for detection and treatment. With next-generation sequencing, we can now map the transcriptional profile of each patient's breast tissue, which has the potential for identifying and characterizi...
Establishment of two pathomic-based machine learning models to predict CLCA1 expression in colon adenocarcinoma.
PloS one
Jul 21, 2025
Chloride channel accessory 1 (CLCA1) is considered a potential prognostic biomarker for colon adenocarcinoma (COAD). The objective of this research was to develop two pathomics models to predict CLCA1 expression from hematoxylin-eosin (H&E) stained p...
Exploration of common pathogenic genes between cerebral amyloid angiopathy and insomnia based on bioinformatics and experimental validation.
Scientific reports
Jul 20, 2025
Cerebral amyloid angiopathy (CAA) and insomnia are age-related neurological disorders increasingly recognized as being closely associated. However, research on the shared genes and their biological mechanisms remains limited. This study aims to ident...
Identification of clinical diagnostic and immune cell infiltration characteristics of acute myocardial infarction with machine learning approach.
Scientific reports
Jul 20, 2025
Acute myocardial infarction (AMI) is a serious heart disease with high fatality rates. The progress of AMI involves immune cell infiltration. However, suitable clinical diagnostic biomarkers and the roles of immune cells in AMI remain unknown. Three ...
Prediction of hub genes in pulpal inflammation and regeneration using autoencoders and a generative AI approach.
Scientific reports
Jul 19, 2025
Pulpal inflammation and regeneration are crucial for enhancing endodontic treatment outcomes. Transcriptomic studies highlight the involvement of proinflammatory cytokines, NF-κB signaling, and stem cell activity. This study employs a generative AI a...
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