AIMC Topic: Transcriptome
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Multi-dimensional characterization of cellular states reveals clinically relevant immunological subtypes and therapeutic vulnerabilities in ovarian cancer.
Journal of translational medicine
May 8, 2025
BACKGROUND: Diverse cell types and cellular states in the tumor microenvironment (TME) are drivers of biological and therapeutic heterogeneity in ovarian cancer (OV). Characterization of the diverse malignant and immunology cellular states that make ...
Transcriptome-wide analysis reveals potential roles of CFD and ANGPTL4 in fibroblasts regulating B cell lineage for extracellular matrix-driven clustering and novel avenues for immunotherapy in breast cancer.
Molecular medicine (Cambridge, Mass.)
May 8, 2025
BACKGROUND: The remodeling of the extracellular matrix (ECM) plays a pivotal role in tumor progression and drug resistance. However, the compositional patterns of ECM in breast cancer and their underlying biological functions remain elusive.
Identification of Hub Genes and Key Pathways Associated with Sepsis Progression Using Weighted Gene Co-Expression Network Analysis and Machine Learning.
International journal of molecular sciences
May 7, 2025
Sepsis is a life-threatening condition driven by dysregulated immune responses, resulting in organ dysfunction and high mortality rates. Identifying key genes and pathways involved in sepsis progression is crucial for improving diagnostic and therape...
Rhythm profiling using COFE reveals multi-omic circadian rhythms in human cancers in vivo.
PLoS biology
May 1, 2025
The study of ubiquitous circadian rhythms in human physiology requires regular measurements across time. Repeated sampling of the different internal tissues that house circadian clocks is both practically and ethically infeasible. Here, we present a ...
Machine learning-augmented m6A-Seq analysis without a reference genome.
Briefings in bioinformatics
May 1, 2025
Methylated RNA m6A immunoprecipitation sequencing (m6A-Seq) is a powerful technique for investigating transcriptome-wide m6A modification. However, most of the existing m6A-Seq protocols rely on reference genomes, limiting their use in species lackin...
Deep scSTAR: leveraging deep learning for the extraction and enhancement of phenotype-associated features from single-cell RNA sequencing and spatial transcriptomics data.
Briefings in bioinformatics
May 1, 2025
Single-cell sequencing has advanced our understanding of cellular heterogeneity and disease pathology, offering insights into cellular behavior and immune mechanisms. However, extracting meaningful phenotype-related features is challenging due to noi...
Oxidative Phosphorylation Pathway in Ankylosing Spondylitis: Multi-Omics Analysis and Machine Learning.
International journal of rheumatic diseases
May 1, 2025
INTRODUCTION: Ankylosing spondylitis (AS) is a chronic inflammatory disease affecting the axial skeleton, characterized by immune microenvironment dysregulation and elevated cytokines like TNF-α and IL-17. Mitochondrial oxidative phosphorylation (OXP...
DTC-m6Am: A Framework for Recognizing N6,2'-O-dimethyladenosine Sites in Unbalanced Classification Patterns Based on DenseNet and Attention Mechanisms.
Frontiers in bioscience (Landmark edition)
Apr 24, 2025
BACKGROUND: mAm is a specific RNA modification that plays an important role in regulating mRNA stability, translational efficiency, and cellular stress response. mAm's precise identification is essential to gain insight into its functional mechanisms...
Analysis of RNA translation with a deep learning architecture provides new insight into translation control.
Nucleic acids research
Apr 10, 2025
Accurate annotation of coding regions in RNAs is essential for understanding gene translation. We developed a deep neural network to directly predict and analyze translation initiation and termination sites from RNA sequences. Trained with human tran...
Machine Learning Unveils Sphingolipid Metabolism's Role in Tumour Microenvironment and Immunotherapy in Lung Cancer.
Journal of cellular and molecular medicine
Apr 1, 2025
TME is a core player in the development of a cancerous lesion, the immune evasive potential of the lesion, and its response to therapy. Sphingolipid metabolism, which governs a number of cellular processes, has been recognised as a player involved in...
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