AIMC Topic: Transcriptome

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Active learning framework leveraging transcriptomics identifies modulators of disease phenotypes.

Science (New York, N.Y.)
Phenotypic drug screening remains constrained by the vastness of chemical space and the technical challenges of scaling experimental workflows. To overcome these barriers, computational methods have been developed to prioritize compounds, but they re...

Single cell and machine learning identify type II pneumocyte-derived biomarkers HN1/OCIAD2/SFTA2 for non-small cell lung cancer prognosis and immune regulation.

European journal of medical research
BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the most prevalent malignancies and currently shows a poor clinical prognosis. Type II pneumocyte, as one of the main sources of cancer cells in NSCLC, is important to explore the molecular fun...

Transcriptomic exploration combined with experimental validation: uncovering the potential value of biomarkers related to ammonia-induced cell death in hepatic ischemia-reperfusion injury.

European journal of medical research
BACKGROUND: Hepatic ischemia-reperfusion injury (HIRI) represents the leading cause of postoperative liver dysfunction and failure. Ammonia-induced cell death (ACD), defined by lysosomal and mitochondrial disruption due to intracellular ammonia accum...

Construction of a novel 3-gene diagnostic signature related to senescence in intervertebral disc degeneration.

European journal of medical research
BACKGROUND: Numerous studies have manifested that cellular senescence involves in the pathogenesis of intervertebral disc degeneration (IDD). Here, we constructed a novel senescence-related genes (SRGs) signature for IDD.

Integrated transcriptomics and proteomics reveal ferroptosis induced by B[a]P and BPDE in mouse hippocampal neurons.

Scientific reports
The environmental pollutant Benzo[a]pyrene (B[a]P) and its ultimate metabolite B[a]P-7,8-diol-9,10-epoxide (BPDE) exhibit neurotoxic effects, yet the underlying molecular mechanisms remain enigmatic. Recently, ferroptosis has emerged as a potential p...

Machine learning driven multiomics analysis identifies disulfidptosis associated molecular subtypes in ovarian cancer.

Scientific reports
Precision oncology enables molecularly guided cancer therapy through multi-omics profiling, AI-driven classification, and biomarker-targeted interventions. Disulfidptosis has emerged as a promising therapeutic target, yet no ovarian cancer classifica...

TGM1 as a novel signature gene in psoriasis identified by integrative bioinformatics and experimental validation.

Molecular medicine reports
Psoriasis is a systemic immune‑mediated skin disease, typically considered to be incurable. Identification of meaningful biomarkers has been a notable challenge in psoriasis prevention and management. The present study aimed to determine the signatur...

Machine learning-enhanced discovery of a basement membrane-related gene signature in glioblastoma via single-cell and Spatial transcriptomics.

Journal of translational medicine
BACKGROUND: The complex invasiveness and heterogeneity of glioblastoma multiforme (GBM) hinder the complete eradication of the tumor. The invasion of the basement membrane (BM) occurs before the spread to the meninges and the metastasis of glioma cel...

Constructing a sixteen lactate-related gene risk signature for LUAD to predict the prognosis and TME by machine learning.

Scientific reports
Although it is the most common subtype of lung cancer in clinical practice, lung adenocarcinoma (LUAD) was proven to be associated with a poor prognosis. In recent years, lactate metabolism has been considered an important biological mechanism in lun...