AIMC Topic: Transcriptome

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Transcriptomic analysis reveals novel targets in benign schwannoma using machine learning.

Neuroscience
BACKGROUND & OBJECTIVE: This study aimed to identify key immune-related biomarkers of benign schwannoma through machine learning-assisted transcriptomic and single-cell analyses, and to construct a predictive model for disease evaluation.

Transcriptomic bioinformatics analysis proposes a novel BCL2-MAPK14-TXN oxidative stress diagnostic model of sepsis and identifies TXN as an oxidative stress-related signature gene in sepsis.

International immunopharmacology
BACKGROUND: Oxidative stress was one of key factors driving the septic development by the uncontrolled accumulation of free radicals, thus oxidative stress-related biomarkers provide a novel diagnostic option. This study focused on screening oxidativ...

WISP2/CCN5 revealed as a potential diagnostic biomarker for endometriosis based on machine learning and single-cell transcriptomic analysis.

Functional & integrative genomics
OBJECTIVE: Endometriosis is a prevalent gynecological disease characterized by the ectopic growth of functional endometrial tissue outside the uterine cavity, affecting millions of women worldwide. Currently, the definitive diagnosis relies on invasi...

Gene expression profiles associated with gray matter and dynamic connectivity disruptions in major depressive disorder.

Journal of affective disorders
PURPOSE: To identify biomarkers linking molecular mechanisms to macroscale brain changes in major depressive disorder (MDD) by integrating multimodal neuroimaging, transcriptomics, and machine learning.

Exploring the over-wintering and over-summering mechanisms of Ulva prolifera from physiological and transcriptome perspectives and their impacts on green tides.

Marine environmental research
Since 2007, the South Yellow Sea region of China has endured the world's largest recurrent green tide disaster for 18 consecutive years, resulting in substantial economic losses and ecological risks. Ulva prolifera the dominant species in these green...

Generative prediction of causal gene sets responsible for complex traits.

Proceedings of the National Academy of Sciences of the United States of America
The relationship between genotype and phenotype remains an outstanding question for organism-level traits because these traits are generally . The challenge arises from complex traits being determined by a combination of multiple genes (or loci), whi...

Exploring the molecular mechanisms of lactylation-related biological functions and immune regulation in sepsis-associated acute kidney injury.

Clinical and experimental medicine
Lactylation, a novel post-translational modification, has been implicated in various pathophysiological processes; however, its role in sepsis-associated acute kidney injury (SA-AKI) remains unclear. This study aimed to investigate the expression pat...

Neurodegeneration Promotes Tumorigenesis in Colorectal Cancer: Insights From Single-Cell and Spatial Multiomics.

JCO precision oncology
PURPOSE: Colorectal cancer (CRC) ranks third in global incidence and second in mortality, with rates increasing among younger populations. The enteric nervous system (ENS) is crucial for gastrointestinal function, and its dysfunction is associated wi...

Measuring natural selection on the transcriptome.

The New phytologist
The level and pattern of gene expression is increasingly recognized as a principal determinant of plant phenotypes and thus of fitness. The estimation of natural selection on the transcriptome is an emerging research discipline. We here review recent...

Machine learning and multi-omics analysis reveal key regulators of proneural-mesenchymal transition in glioblastoma.

Scientific reports
Glioblastoma (GBM) is classified into subtypes according to the molecular expression profile; the proneural subtype has a relatively good prognosis, and the mesenchymal type is the most aggressive form with the worst prognosis. GBM undergoes proneura...