AIMC Topic: Transcriptome

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Analyses of the mechanism and therapeutic targets of senescence related genes in ischemic stroke with multi-omics approach.

Scientific reports
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
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
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
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
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
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...

Comparative machine learning analysis for predicting organ tropism in breast cancer and identifying key gene signatures.

Computers in biology and medicine
BACKGROUND: Breast cancer metastasis (BCM) metastasizes preferentially to certain organs. Important genetic markers can be used for early detection and treatment. Machine learning (ML) can efficiently handle gene expression data to enhance metastasis...

Biomarker discovery for early breast cancer diagnosis using machine learning on transcriptomic data for biosensor development.

Computers in biology and medicine
Breast cancer is the second leading cause of female mortality globally. Effective diagnostic tools, such as biosensors that utilize reliable biomarkers, are essential for early detection, particularly in low-income countries. This study introduces a ...

Diagnostic immune-related markers for diabetic kidney disease: a bioinformatics and machine learning approach.

Renal failure
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...

Single-cell spatial transcriptomics reveals immunotherapy-driven bone marrow niche remodeling in AML.

Science advances
Given the graft-versus-leukemia effect observed with allogeneic hematopoietic stem cell transplantation in refractory or relapsed acute myeloid leukemia (AML), immunotherapies have been explored in nontransplant settings. We applied a multiomic appro...