AIMC Topic: Genes, Mitochondrial
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Comprehensive bioinformatics analysis and experimental verification identify mitochondrial gene Dgat2 as a novel therapeutic biomarker for myocardial ischemia-reperfusion.
Frontiers in endocrinology
May 29, 2025
BACKGROUND: Ischemic cardiomyopathy is a severe disease marked by high morbidity and mortality, often exacerbated by myocardial ischemia/reperfusion injury (MI/RI). Mitochondrial metabolism plays a critical role in MI/RI progression. This study aimed...
Identification and verification of mitochondria-related genes biomarkers associated with immune infiltration for COPD using WGCNA and machine learning algorithms.
Scientific reports
Apr 24, 2025
Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated wi...
Machine learning-based algorithm identifies key mitochondria-related genes in non-alcoholic steatohepatitis.
Lipids in health and disease
May 8, 2024
BACKGROUND: Evidence suggests that hepatocyte mitochondrial dysfunction leads to abnormal lipid metabolism, redox imbalance, and programmed cell death, driving the onset and progression of non-alcoholic steatohepatitis (NASH). Identifying hub mitocho...
Machine-learning prediction of a novel diagnostic model using mitochondria-related genes for patients with bladder cancer.
Scientific reports
Apr 23, 2024
Bladder cancer (BC) is the ninth most-common cancer worldwide and it is associated with high morbidity and mortality. Mitochondrial Dysfunction is involved in the progression of BC. This study aimed to developed a novel diagnostic model based on mito...
Exploring a novel seven-gene marker and mitochondrial gene TMEM38A for predicting cervical cancer radiotherapy sensitivity using machine learning algorithms.
Frontiers in endocrinology
Jan 24, 2024
BACKGROUND: Radiotherapy plays a crucial role in the management of Cervical cancer (CC), as the development of resistance by cancer cells to radiotherapeutic interventions is a significant factor contributing to treatment failure in patients. However...
MitoScape: A big-data, machine-learning platform for obtaining mitochondrial DNA from next-generation sequencing data.
PLoS computational biology
Nov 11, 2021
The growing number of next-generation sequencing (NGS) data presents a unique opportunity to study the combined impact of mitochondrial and nuclear-encoded genetic variation in complex disease. Mitochondrial DNA variants and in particular, heteroplas...
DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data.
Nature communications
Oct 6, 2021
Feature selection (marker gene selection) is widely believed to improve clustering accuracy, and is thus a key component of single cell clustering pipelines. Existing feature selection methods perform inconsistently across datasets, occasionally even...
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