AIMC Topic: Transcriptome
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Transcriptome analysis and machine learning methods reveal potential mechanisms of zebrafish muscle aging.
Comparative biochemistry and physiology. Part D, Genomics & proteomics
Sep 1, 2025
Muscle is one of the most abundant tissues in the human body, and its aging usually leads to many adverse consequences. Zebrafish is a powerful model used to study human muscle diseases, yet we know little about the molecular mechanisms of muscle agi...
Combining Spatial Transcriptomics, Pseudotime, and Machine Learning Enables Discovery of Biomarkers for Prostate Cancer.
Cancer research
Jul 2, 2025
UNLABELLED: Early cancer diagnosis is crucial but challenging owing to the lack of reliable biomarkers that can be measured using routine clinical methods. The identification of biomarkers for early detection is complicated by each tumor involving ch...
Global Thyroid Cancer Patterns and Predictive Analytics: Integrating Machine Learning for Advanced Diagnostic Modelling.
Journal of cellular and molecular medicine
Jul 1, 2025
BACKGROUND: The global increase in thyroid cancer prevalence, particularly among female populations, underscores critical gaps in our understanding of molecular pathogenesis and diagnostic capabilities. Our investigation addresses these knowledge def...
Application of a metabolic network-based graph neural network for the identification of toxicant-induced perturbations.
Toxicological sciences : an official journal of the Society of Toxicology
Jul 1, 2025
Transcriptomic analyses have been an effective approach to investigate the biological responses and metabolic perturbations by environmental contaminants in rodent models. However, it is well recognized that metabolic networks are highly connected an...
Sepsis Important Genes Identification Through Biologically Informed Deep Learning and Transcriptomic Analysis.
Clinical and experimental pharmacology & physiology
Jul 1, 2025
Sepsis is a life-threatening disease caused by the dysregulation of the immune response. It is important to identify influential genes modulating the immune response in sepsis. In this study, we used P-NET, a biologically informed explainable artific...
Mesenchymal stem cell transplantation ameliorates inflammation in spinal cord injury by inhibiting lactylation-related genes.
Cytokine
Jul 1, 2025
BACKGROUND: The immune microenvironment significantly influences neural regeneration in spinal cord injury (SCI). Lactate activates central nervous system (CNS) glial cells, prompting the secretion of proinflammatory cytokines and triggering an infla...
Deciphering the Regulatory Networks of the Migrasome-Associated Cell Subpopulation in Heterotopic Ossification via Multi-Omics Analysis.
FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Jun 30, 2025
Heterotopic ossification (HO) is a pathological process where bone forms in extraskeletal tissues, often occurring as a complication of tissue repair following injury. This condition can lead to movement limitations, pain, and functional impairment. ...
Neuroimaging pattern interactions for suicide risk in depression captured by ensemble learning over transcriptome-defined parcellation.
Progress in neuro-psychopharmacology & biological psychiatry
Jun 20, 2025
BACKGROUND: For suicide in major depression disorder, it is urgent to seek for a reliable neuroimaging biomarker with interpretable links to molecular tissue signatures. Accordingly, we developed an ensemble learning scheme over transcriptome-defined...
Unveiling the systemic impact of airborne microplastics: Integrating breathomics and machine learning with dual-tissue transcriptomics.
Journal of hazardous materials
Jun 15, 2025
Airborne microplastics (MPs) pose significant respiratory and systemic health risks upon inhalation; however, current assessment methods remain inadequate. This study integrates breathomics and transcriptomics to establish a non-invasive approach for...
Artificial intelligence approaches for tumor phenotype stratification from single-cell transcriptomic data.
eLife
Jun 13, 2025
Single-cell RNA-sequencing (scRNA-seq) coupled with robust computational analysis facilitates the characterization of phenotypic heterogeneity within tumors. Current scRNA-seq analysis pipelines are capable of identifying a myriad of malignant and no...
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