AIMC Topic: Transcriptome
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Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning.
Frontiers in immunology
Mar 21, 2025
BACKGROUND: Recent studies have suggested a potential association between gastric cancer (GC) and myocardial infarction (MI), with shared pathogenic factors. This study aimed to identify these common factors and potential pharmacologic targets.
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility.
PLoS genetics
Mar 19, 2025
Deep learning techniques are increasingly utilized to analyze large-scale single-cell RNA sequencing (scRNA-seq) data, offering valuable insights from complex transcriptome datasets. Geneformer, a pre-trained model using a Transformer Encoder archite...
A multimodal framework for assessing the link between pathomics, transcriptomics, and pancreatic cancer mutations.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 15, 2025
In Pancreatic Ductal Adenocarcinoma (PDAC), predicting genetic mutations directly from histopathological images using Deep Learning can provide valuable insights. The combination of several omics can provide further knowledge on mechanisms underlying...
Defining lipedema's molecular hallmarks by multi-omics approach for disease prediction in women.
Metabolism: clinical and experimental
Mar 15, 2025
Lipedema is a chronic disease in females characterized by pathologic subcutaneous adipose tissue expansion and hitherto remains without druggable targets. In this observational study, we investigated the molecular hallmarks of lipedema using an unbia...
Screening necroptosis genes influencing osteoarthritis development based on machine learning.
Scientific reports
Mar 15, 2025
Machine learning can be applied to identify key genes associated with osteoarthritis (OA). This study aimed to explore the differential expression of necroptosis-related genes (NRGs) during the progression of OA, identify key gene modules strongly li...
Multi-omics integration and machine learning identify and validate neutrophil extracellular trap-associated gene signatures in chronic rhinosinusitis with nasal polyps.
Clinical immunology (Orlando, Fla.)
Mar 13, 2025
This study aimed to explore the molecular characteristics of neutrophil extracellular traps (NETs) in chronic rhinosinusitis with nasal polyps (CRSwNP). Differentially expressed gene analysis, weighted gene co-expression network analysis, and machine...
MuCST: restoring and integrating heterogeneous morphology images and spatial transcriptomics data with contrastive learning.
Genome medicine
Mar 13, 2025
Spatially resolved transcriptomics (SRT) simultaneously measure spatial location, histology images, and transcriptional profiles of cells or regions in undissociated tissues. Integrative analysis of multi-modal SRT data holds immense potential for un...
Comprehensive integration of diagnostic biomarker analysis and immune cell infiltration features in sepsis via machine learning and bioinformatics techniques.
Frontiers in immunology
Mar 10, 2025
INTRODUCTION: Sepsis, a critical medical condition resulting from an irregular immune response to infection, leads to life-threatening organ dysfunction. Despite medical advancements, the critical need for research into dependable diagnostic markers ...
Machine learning uncovers the transcriptional regulatory network for the production host Streptomyces albidoflavus.
Cell reports
Mar 8, 2025
Streptomyces albidoflavus is a widely used strain for natural product discovery and production through heterologous biosynthetic gene clusters (BGCs). However, the transcriptional regulatory network (TRN) and its impact on secondary metabolism remain...
Screening and validating genes associated with cuproptosis in systemic lupus erythematosus by expression profiling combined with machine learning.
Biomolecules & biomedicine
Mar 7, 2025
Cell death has long been a focal point in life sciences research, and recently, scientists have discovered a novel form of cell death induced by copper, termed cuproptosis. This paper aimed to identify genes associated with cuproptosis in systemic lu...
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