AIMC Topic: Metabolic Networks and Pathways

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A machine learning framework for extracting information from biological pathway images in the literature.

Metabolic engineering Sep 2, 2024
There have been significant advances in literature mining, allowing for the extraction of target information from the literature. However, biological literature often includes biological pathway images that are difficult to extract in an easily edita...
Machine Learning Metabolic Networks and Pathways Data Mining
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Metabolomics Unveils Disrupted Pathways in Parkinson's Disease: Toward Biomarker-Based Diagnosis.

ACS chemical neuroscience Aug 23, 2024
Parkinson's disease (PD) is a neurodegenerative disorder characterized by diverse symptoms, where accurate diagnosis remains challenging. Traditional clinical observation methods often result in misdiagnosis, highlighting the need for biomarker-based...
Brazil Humans Metabolomics Machine Learning Caffeine Parkinson Disease Male Female Hypoxanthine Middle Aged Aged Metabolic Networks and Pathways Biomarkers
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Identification of key metabolism-related genes and pathways in spontaneous preterm birth: combining bioinformatic analysis and machine learning.

Frontiers in endocrinology Aug 20, 2024
BACKGROUND: Spontaneous preterm birth (sPTB) is a global disease that is a leading cause of death in neonates and children younger than 5 years of age. However, the etiology of sPTB remains poorly understood. Recent evidence has shown a strong associ...
Premature Birth Pregnancy Metabolic Networks and Pathways Gene Expression Profiling Female Computational Biology Placenta Infant, Newborn Databases, Genetic Gene Regulatory Networks Humans Machine Learning
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Gtie-Rt: A comprehensive graph learning model for predicting drugs targeting metabolic pathways in human.

Journal of bioinformatics and computational biology Jul 20, 2024
Drugs often target specific metabolic pathways to produce a therapeutic effect. However, these pathways are complex and interconnected, making it challenging to predict a drug's potential effects on an organism's overall metabolism. The mapping of dr...
Neural Networks, Computer Machine Learning Algorithms Humans Pharmaceutical Preparations Computational Biology Models, Biological Metabolic Networks and Pathways Drug Interactions
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Construction of an enzyme-constrained metabolic network model for Myceliophthora thermophila using machine learning-based k data.

Microbial cell factories May 15, 2024
BACKGROUND: Genome-scale metabolic models (GEMs) serve as effective tools for understanding cellular phenotypes and predicting engineering targets in the development of industrial strain. Enzyme-constrained genome-scale metabolic models (ecGEMs) have...
Genome, Fungal Metabolic Engineering Sordariales Metabolic Networks and Pathways Kinetics Models, Biological Machine Learning Biomass
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Genome-scale metabolic models in translational medicine: the current status and potential of machine learning in improving the effectiveness of the models.

Molecular omics May 7, 2024
The genome-scale metabolic model (GEM) has emerged as one of the leading modeling approaches for systems-level metabolic studies and has been widely explored for a broad range of organisms and applications. Owing to the development of genome sequenci...
Models, Biological Translational Research, Biomedical Genome Animals Metabolic Networks and Pathways Translational Science, Biomedical Humans Machine Learning
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A cautionary tale about properly vetting datasets used in supervised learning predicting metabolic pathway involvement.

PloS one May 2, 2024
The mapping of metabolite-specific data to pathways within cellular metabolism is a major data analysis step needed for biochemical interpretation. A variety of machine learning approaches, particularly deep learning approaches, have been used to pre...
Humans Metabolic Networks and Pathways Datasets as Topic Supervised Machine Learning
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Machine learning enables identification of an alternative yeast galactose utilization pathway.

Proceedings of the National Academy of Sciences of the United States of America Apr 26, 2024
How genomic differences contribute to phenotypic differences is a major question in biology. The recently characterized genomes, isolation environments, and qualitative patterns of growth on 122 sources and conditions of 1,154 strains from 1,049 fung...
Machine Learning Metabolic Networks and Pathways Saccharomyces cerevisiae Genome, Fungal Galactose
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Deciphering Ferroptosis: From Molecular Pathways to Machine Learning-Guided Therapeutic Innovation.

Molecular biotechnology Apr 13, 2024
Ferroptosis is a unique form of cell death reliant on iron and lipid peroxidation. It disrupts redox balance, causing cell death by damaging the plasma membrane, with inducers acting through enzymatic pathways or transport systems. In cancer treatmen...
Signal Transduction Ferroptosis Iron Lipid Peroxidation Biomarkers Humans Metabolic Networks and Pathways Animals Machine Learning Neoplasms
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Using metabolic networks to predict cross-feeding and competition interactions between microorganisms.

Microbiology spectrum Mar 20, 2024
Understanding the interactions between microorganisms and their impact on bacterial behavior at the community level is a key research topic in microbiology. Different methods, relying on experimental or mathematical approaches based on the diverse pr...
Microbial Interactions Bacterial Physiological Phenomena Microbial Consortia Support Vector Machine Metabolic Networks and Pathways Algorithms Bacteria Computational Biology Machine Learning
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