AIMC Topic: PPAR gamma

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Prospective de novo drug design with deep interactome learning.

Nature communications Apr 22, 2024
De novo drug design aims to generate molecules from scratch that possess specific chemical and pharmacological properties. We present a computational approach utilizing interactome-based deep learning for ligand- and structure-based generation of dru...
Ligands Deep Learning PPAR gamma Protein Binding Humans Binding Sites Drug Design
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Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach.

Chemical research in toxicology Jun 7, 2019
Exposure to certain chemicals such as disinfectants through inhalation is suspected to be involved in the development of pulmonary fibrosis, a lung disease in which lung tissue becomes damaged and scarred. Pulmonary fibrosis is known to be regulated ...
Neural Networks, Computer Databases, Factual Humans Toxicity Tests PPAR gamma Adverse Outcome Pathways Deep Learning Pulmonary Fibrosis
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Interaction of Vitamin E Intake and Pro12Ala Polymorphism of PPARG with Adiponectin Levels.

Journal of nutrigenetics and nutrigenomics Feb 2, 2018
BACKGROUND/AIM: One of the beneficial effects associated with vitamin E intake is the enhancement of peroxisome proliferator-activated receptor gamma (PPARγ) activity and the consequent upregulation of adiponectin expression. The aim of this study wa...
Adiponectin Amino Acid Substitution Cross-Sectional Studies Vitamin E Polymorphism, Single Nucleotide Male Young Adult Genotype Humans Middle Aged Adult Nutrigenomics Female Adolescent PPAR gamma
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Machine learning shows association between genetic variability in and cerebral connectivity in preterm infants.

Proceedings of the National Academy of Sciences of the United States of America Dec 11, 2017
Preterm infants show abnormal structural and functional brain development, and have a high risk of long-term neurocognitive problems. The molecular and cellular mechanisms involved are poorly understood, but novel methods now make it possible to addr...
Integrin alpha6 Infant, Premature Connectome PPAR gamma Diffusion Tensor Imaging Polymorphism, Single Nucleotide RNA-Binding Proteins Infant, Newborn Male Humans Brain Female Machine Learning
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Integration of metabolomics, lipidomics and clinical data using a machine learning method.

BMC bioinformatics Nov 22, 2016
BACKGROUND: The recent pandemic of obesity and the metabolic syndrome (MetS) has led to the realisation that new drug targets are needed to either reduce obesity or the subsequent pathophysiological consequences associated with excess weight gain. Ce...
Rats, Sprague-Dawley Metabolic Syndrome Metabolomics Liver Male Rats Humans Databases, Factual Machine Learning PPAR gamma Animals Blood Chemical Analysis PPAR alpha Obesity Lipid Metabolism
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Unveiling the glycolysis in sepsis: Integrated bioinformatics and machine learning analysis identifies crucial roles for IER3, DSC2, and PPARG in disease pathogenesis.

Medicine Sep 27, 2024
Sepsis, a multifaceted syndrome driven by an imbalanced host response to infection, remains a significant medical challenge. At its core lies the pivotal role of glycolysis, orchestrating immune responses especially in severe sepsis. The intertwined ...
Male Middle Aged Machine Learning Female Glycolysis Computational Biology PPAR gamma Transcriptome Sepsis Humans
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