AIMC Topic: Mitochondria
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Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.
Frontiers in endocrinology
Mar 27, 2025
PURPOSE: We aimed to identify the mitochondria-related feature genes associated with type 2 diabetes mellitus and explore their potential roles in immune cell infiltration.
Machine learning-derived prognostic signature integrating programmed cell death and mitochondrial function in renal clear cell carcinoma: identification of PIF1 as a novel target.
Cancer immunology, immunotherapy : CII
Feb 25, 2025
BACKGROUND: The pathogenesis and progression of renal cell carcinoma (RCC) involve complex programmed cell death (PCD) processes. As the powerhouse of the cell, mitochondria can influence cell death mechanisms. However, the prognostic significance of...
Atrial fibrillation risk model based on LASSO and SVM algorithms and immune infiltration of key mitochondrial energy metabolism genes.
Scientific reports
Feb 24, 2025
Atrial fibrillation (AF) is a predominant cardiac arrhythmia with unclear etiology. This study used bioinformatics and machine learning to explore the relationship between mitochondrial energy metabolism-related genes (MEMRGs) and immune infiltration...
A hybrid machine learning framework for functional annotation of mitochondrial glutathione transport and metabolism proteins in cancers.
BMC bioinformatics
Feb 11, 2025
BACKGROUND: Alterations of metabolism, including changes in mitochondrial metabolism as well as glutathione (GSH) metabolism are a well appreciated hallmark of many cancers. Mitochondrial GSH (mGSH) transport is a poorly characterized aspect of GSH m...
Integrating mitochondrial and lysosomal gene analysis for breast cancer prognosis using machine learning.
Scientific reports
Jan 27, 2025
The impact of mitochondrial and lysosomal co-dysfunction on breast cancer patient outcomes is unclear. The objective of this study is to develop a predictive machine learning (ML) model utilizing mitochondrial and lysosomal co-regulators in order to ...
Mitochondrial segmentation and function prediction in live-cell images with deep learning.
Nature communications
Jan 16, 2025
Mitochondrial morphology and function are intrinsically linked, indicating the opportunity to predict functions by analyzing morphological features in live-cell imaging. Herein, we introduce MoDL, a deep learning algorithm for mitochondrial image seg...
Machine learning identified novel players in lipid metabolism, endosomal trafficking, and iron metabolism of the ALS spinal cord.
Scientific reports
Jan 10, 2025
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease affecting motor neurons. Although genes causing familial cases have been identified, those of sporadic ALS, which occupies the majority of patients, are still elusive. In this s...
Attention-based deep learning for accurate cell image analysis.
Scientific reports
Jan 8, 2025
High-content analysis (HCA) holds enormous potential for drug discovery and research, but widely used methods can be cumbersome and yield inaccurate results. Noisy and redundant signals in cell images impede accurate deep learning-based image analysi...
Identification of immune-related mitochondrial metabolic disorder genes in septic shock using bioinformatics and machine learning.
Hereditas
Nov 28, 2024
PURPOSE: Mitochondria are involved in septic shock and inflammatory response syndrome, which severely affects the life security of patients. It is necessary to recognize and explore the immune-mitochondrial genes in septic shock.
Deep learning-enhanced automated mitochondrial segmentation in FIB-SEM images using an entropy-weighted ensemble approach.
PloS one
Nov 26, 2024
Mitochondria are intracellular organelles that act as powerhouses by breaking down nutrition molecules to produce adenosine triphosphate (ATP) as cellular fuel. They have their own genetic material called mitochondrial DNA. Alterations in mitochondri...
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