AIMC Topic: Xenobiotics

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Machine learning algorithm-based risk prediction model of coronary artery disease.

Molecular biology reports Jul 11, 2018
In view of high mortality associated with coronary artery disease (CAD), development of an early predicting tool will be beneficial in reducing the burden of the disease. The database comprising demographic, conventional, folate/xenobiotic genetic ri...
Machine Learning Algorithms Forecasting Humans Cytochrome P-450 CYP1A1 Glycine Hydroxymethyltransferase Epistasis, Genetic Multifactor Dimensionality Reduction Xenobiotics Middle Aged Case-Control Studies Genetic Predisposition to Disease Polymorphism, Single Nucleotide Coronary Artery Disease Folic Acid Aged Adult Male Female Risk Factors
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Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

Archives of toxicology Apr 28, 2018
Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide ...
A549 Cells High-Throughput Screening Assays Toxicity Tests Cell Survival Predictive Value of Tests Bronchi Xenobiotics Humans Artificial Intelligence Sensitivity and Specificity Lung Cell Line
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FAME 2: Simple and Effective Machine Learning Model of Cytochrome P450 Regioselectivity.

Journal of chemical information and modeling Aug 7, 2017
UNLABELLED: We report on the further development of FAst MEtabolizer (FAME; J. Chem. Inf.
Xenobiotics Cytochrome P-450 Enzyme System Stereoisomerism Substrate Specificity Software Computational Biology Machine Learning
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Artificial neural network-based exploration of gene-nutrient interactions in folate and xenobiotic metabolic pathways that modulate susceptibility to breast cancer.

Gene Jan 16, 2016
In the current study, an artificial neural network (ANN)-based breast cancer prediction model was developed from the data of folate and xenobiotic pathway genetic polymorphisms along with the nutritional and demographic variables to investigate how m...
Humans Neural Networks, Computer Female Aged Adult Breast Neoplasms Disease Susceptibility Food Epistasis, Genetic Gene-Environment Interaction Xenobiotics Computational Biology Metabolic Networks and Pathways Folic Acid Middle Aged Diet Case-Control Studies
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Multifactor dimensionality reduction analysis to elucidate the cross-talk between one-carbon and xenobiotic metabolic pathways in multi-disease models.

Molecular biology reports Feb 4, 2015
Putatively functional polymorphisms of one-carbon and xenobiotic metabolic pathways influence susceptibility for wide spectrum of diseases. The current study was aimed to explore gene-gene interactions among these two metabolic pathways in four disea...
Sex Factors Datasets as Topic Gene Expression Regulation Lupus Erythematosus, Systemic Coronary Artery Disease Multifactor Dimensionality Reduction Xenobiotics Epistasis, Genetic Oxidoreductases Transferases Genetic Predisposition to Disease Polymorphism, Single Nucleotide Carbon Parkinson Disease Metabolic Networks and Pathways Factor Analysis, Statistical Breast Neoplasms Male Case-Control Studies Humans Female
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Applying machine learning techniques for ADME-Tox prediction: a review.

Expert opinion on drug metabolism & toxicology Dec 2, 2014
INTRODUCTION: Pharmacokinetics involves the study of absorption, distribution, metabolism, excretion and toxicity of xenobiotics (ADME-Tox). In this sense, the ADME-Tox profile of a bioactive compound can impact its efficacy and safety. Moreover, eff...
Models, Biological Quantitative Structure-Activity Relationship Xenobiotics Artificial Intelligence Drug Design Humans
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XenoBug: machine learning-based tool to predict pollutant-degrading enzymes from environmental metagenomes.

NAR genomics and bioinformatics Jun 1, 2025
Application of machine learning-based methods to identify novel bacterial enzymes capable of degrading a wide range of xenobiotics offers enormous potential for bioremediation of toxic and carcinogenic recalcitrant xenobiotics such as pesticides, pla...
Machine Learning Metagenomics Xenobiotics Metagenome Bacteria Environmental Pollutants Biodegradation, Environmental
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