AIMC Topic: Glycolysis
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Dynamic mode decomposition for analysis and prediction of metabolic oscillations from time-lapse imaging of cellular autofluorescence.
Scientific reports
Jul 2, 2025
Oscillations are a common phenomenon in cell biology. They are based on non-linear coupling of biochemical reactions and can show rich dynamic behavior as found in, for example, glycolysis of yeast cells. Here, we show that dynamic mode decomposition...
Bioinformatics Approach to Identifying Molecular Targets of Isoliquiritigenin Affecting Chronic Obstructive Pulmonary Disease: A Machine Learning Pharmacology Study.
International journal of molecular sciences
Apr 21, 2025
To identify the molecular targets and possible mechanisms of isoliquiritigenin (ISO) in affecting chronic obstructive pulmonary disease (COPD) by regulating the glycolysis and phagocytosis of alveolar macrophages (AM). Datasets GSE130928 and GSE13896...
Machine learning reveals glycolytic key gene in gastric cancer prognosis.
Scientific reports
Mar 13, 2025
Glycolysis is recognized as a central metabolic pathway in the neoplastic evolution of gastric cancer, exerting profound effects on the tumor microenvironment and the neoplastic growth trajectory. However, the identification of key glycolytic genes t...
Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence.
Frontiers in immunology
Jan 23, 2025
BACKGROUND: Diabetic nephropathy (DN) is a complication of systemic microvascular disease in diabetes mellitus. Abnormal glycolysis has emerged as a potential factor for chronic renal dysfunction in DN. The current lack of reliable predictive biomark...
Uncovering glycolysis-driven molecular subtypes in diabetic nephropathy: a WGCNA and machine learning approach for diagnostic precision.
Biology direct
Jan 21, 2025
INTRODUCTION: Diabetic nephropathy (DN) is a common diabetes-related complication with unclear underlying pathological mechanisms. Although recent studies have linked glycolysis to various pathological states, its role in DN remains largely underexpl...
Metabolic Fluxes Using Deep Learning Based on Enzyme Variations: .
International journal of molecular sciences
Dec 13, 2024
Metabolic pathway modeling, essential for understanding organism metabolism, is pivotal in predicting genetic mutation effects, drug design, and biofuel development. Enhancing these modeling techniques is crucial for achieving greater prediction accu...
Identification of glycolysis genes signature for predicting prognosis in malignant pleural mesothelioma by bioinformatics and machine learning.
Frontiers in endocrinology
Nov 29, 2022
BACKGROUND: Glycolysis-related genes as prognostic markers in malignant pleural mesothelioma (MPM) is still unclear. We hope to explore the relationship between glycolytic pathway genes and MPM prognosis by constructing prognostic risk models through...
The proteome landscape of the kingdoms of life.
Nature
Jun 17, 2020
Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported, ...
Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma.
European radiology
Jun 10, 2020
OBJECTIVE: To assess the utility of deep learning analysis using F-fluorodeoxyglucose (FDG) uptake by positron emission tomography (PET/CT) to predict disease-free survival (DFS) in patients with oral cavity squamous cell carcinoma (OCSCC).
Humans
Algorithms
Reproducibility of Results
Aged
Retrospective Studies
Female
Kaplan-Meier Estimate
Glycolysis
Disease-Free Survival
Treatment Outcome
Tumor Burden
Squamous Cell Carcinoma of Head and Neck
Fluorodeoxyglucose F18
Neoplasm Staging
Mouth Neoplasms
Predictive Value of Tests
Positron Emission Tomography Computed Tomography
Male
Middle Aged
Diagnosis, Computer-Assisted
Deep Learning
Aged, 80 and over
Adult
Sensitivity and Specificity
Flux prediction using artificial neural network (ANN) for the upper part of glycolysis.
PloS one
May 8, 2019
The selection of optimal enzyme concentration in multienzyme cascade reactions for the highest product yield in practice is very expensive and time-consuming process. The modelling of biological pathways is a difficult process because of the complexi...
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