AIMC Topic: Transcriptome
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scMalignantFinder distinguishes malignant cells in single-cell and spatial transcriptomics by leveraging cancer signatures.
Communications biology
Mar 27, 2025
Single-cell RNA sequencing (scRNA-seq) is a powerful tool for characterizing tumor heterogeneity, yet accurately identifying malignant cells remains challenging. Here, we propose scMalignantFinder, a machine learning tool specifically designed to dis...
Integrating machine learning and multi-omics analysis to reveal nucleotide metabolism-related immune genes and their functional validation in ischemic stroke.
Frontiers in immunology
Mar 26, 2025
BACKGROUND: Ischemic stroke (IS) is a major global cause of death and disability, linked to nucleotide metabolism imbalances. This study aimed to identify nucleotide metabolism-related genes associated with IS and explore their roles in disease mecha...
Identification of glucocorticoid-related genes in systemic lupus erythematosus using bioinformatics analysis and machine learning.
PloS one
Mar 25, 2025
BACKGROUND: Systemic lupus erythematosus (SLE) is a complex autoimmune disease that has significant impacts on patients' quality of life and poses a substantial economic burden on society.
Identification of novel inflammatory response-related biomarkers in patients with ischemic stroke based on WGCNA and machine learning.
European journal of medical research
Mar 22, 2025
BACKGROUND: Ischemic stroke (IS) is one of the most common causes of disability in adults worldwide. This study aimed to identify key genes related to the inflammatory response to provide insights into the mechanisms and management of IS.
Systems biology of Haemonchus contortus - Advancing biotechnology for parasitic nematode control.
Biotechnology advances
Mar 22, 2025
Parasitic nematodes represent a substantial global burden, impacting animal health, agriculture and economies worldwide. Of these worms, Haemonchus contortus - a blood-feeding nematode of ruminants - is a major pathogen and a model for molecular and ...
Incorporating time as a third dimension in transcriptomic analysis using machine learning and explainable AI.
Computational biology and chemistry
Mar 21, 2025
Transcriptomic data analysis entails the measurement of RNA transcript (gene expression products) abundance in a cell or a cell population at a single point in time. In other words, transcriptomics as it is currently practiced is two-dimensional (2DT...
scVAEDer: integrating deep diffusion models and variational autoencoders for single-cell transcriptomics analysis.
Genome biology
Mar 21, 2025
Discovering a lower-dimensional embedding of single-cell data can improve downstream analysis. The embedding should encapsulate both the high-level features and low-level variations. While existing generative models attempt to learn such low-dimensio...
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...
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