AIMC Topic: Transcriptome
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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...
STHD: probabilistic cell typing of single spots in whole transcriptome spatial data with high definition.
Genome biology
Jul 18, 2025
Recent advances in spatial transcriptomics technologies have enabled gene expression profiling across the transcriptome in spots with subcellular resolution, but high sparsity and dimensionality present significant computational challenges. We presen...
Using machine learning to discover DNA metabolism biomarkers that direct prostate cancer treatment.
Scientific reports
Jul 18, 2025
DNA metabolism genes play pivotal roles in the regulation of cellular processes that contribute to cancer progression, immune modulation, and therapeutic response in prostate cancer (PC). Understanding the mechanisms by which these genes influence th...
Analyses of the mechanism and therapeutic targets of senescence related genes in ischemic stroke with multi-omics approach.
Scientific reports
Jul 18, 2025
Ischemic stroke (IS) affects 11 million people annually, posing substantial clinical and economic burdens. Current therapies remain limited by time sensitivity and variable efficacy, necessitating novel biomarkers. We developed a multi-omics framewor...
Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings.
Nature communications
Jul 18, 2025
Single-cell spatial transcriptomics can provide subcellular resolution for a deep understanding of molecular mechanisms. However, accurate segmentation and annotation remain a major challenge that limits downstream analysis. Current machine learning ...
Image-based inference of tumor cell trajectories enables large-scale cancer progression analysis.
Science advances
Jul 18, 2025
Current approaches to estimating cell trajectories, tumor progression dynamics, and cell population diversity of tumor microenvironment often depend on single-cell RNA sequencing, which is costly and resource intensive. To address this limitation, we...
Multi-transcriptomics predicts clinical outcome in systemically untreated breast cancer patients with extensive follow-up.
Breast cancer research : BCR
Jul 15, 2025
BACKGROUND: Prognostic tools for determining patients with indolent breast cancers (BCs) are far from optimal, leading to extensive overtreatment. Several studies have demonstrated mRNAs, lncRNAs and miRNAs to have prognostic potential in BC. Because...
Exploring novel molecular mechanisms underlying recurrent pregnancy loss in decidual tissues.
Scientific reports
Jul 15, 2025
Recurrent pregnancy loss (RPL), which affects approximately 2.5% of reproductive-aged women, remains idiopathic in more than 50% of cases, necessitating mechanistic insights and biomarkers. Three RPL decidual tissue transcriptomic datasets (GSE113790...
Integrated bioinformatics and machine learning reveal key genes and immune mechanisms associated with uremia.
Scientific reports
Jul 14, 2025
Uremia is a serious complication of end-stage chronic kidney disease, closely associated with immune imbalance and chronic inflammation. However, its molecular mechanisms remain largely unclear. In this study, we analyzed transcriptomic data from the...
Diagnostic immune-related markers for diabetic kidney disease: a bioinformatics and machine learning approach.
Renal failure
Jul 10, 2025
OBJECTIVE: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease, with chronic inflammation driving its progression. This study aimed to identify immune-related diagnostic biomarkers for DKD and explore their association with imm...
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