AIMC Topic: Metabolome

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Effect of congenital adrenal hyperplasia treated by glucocorticoids on plasma metabolome: a machine-learning-based analysis.

Scientific reports
BACKGROUND: Congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency leads to impaired cortisol biosynthesis. Treatment includes glucocorticoid supplementation. We studied the specific metabolomics signatures in CAH patients using two di...

Untargeted Metabolomics for Metabolic Diagnostic Screening with Automated Data Interpretation Using a Knowledge-Based Algorithm.

International journal of molecular sciences
Untargeted metabolomics may become a standard approach to address diagnostic requests, but, at present, data interpretation is very labor-intensive. To facilitate its implementation in metabolic diagnostic screening, we developed a method for automat...

An unsupervised learning approach to identify novel signatures of health and disease from multimodal data.

Genome medicine
BACKGROUND: Modern medicine is rapidly moving towards a data-driven paradigm based on comprehensive multimodal health assessments. Integrated analysis of data from different modalities has the potential of uncovering novel biomarkers and disease sign...

Antibiotic resistance and metabolic profiles as functional biomarkers that accurately predict the geographic origin of city metagenomics samples.

Biology direct
BACKGROUND: The availability of hundreds of city microbiome profiles allows the development of increasingly accurate predictors of the origin of a sample based on its microbiota composition. Typical microbiome studies involve the analysis of bacteria...

Understanding mixed environmental exposures using metabolomics via a hierarchical community network model in a cohort of California women in 1960's.

Reproductive toxicology (Elmsford, N.Y.)
Even though the majority of population studies in environmental health focus on a single factor, environmental exposure in the real world is a mixture of many chemicals. The concept of "exposome" leads to an intellectual framework of measuring many e...

Classification of alkaloids according to the starting substances of their biosynthetic pathways using graph convolutional neural networks.

BMC bioinformatics
BACKGROUND: Alkaloids, a class of organic compounds that contain nitrogen bases, are mainly synthesized as secondary metabolites in plants and fungi, and they have a wide range of bioactivities. Although there are thousands of compounds in this class...

Discovery of food identity markers by metabolomics and machine learning technology.

Scientific reports
Verification of food authenticity establishes consumer trust in food ingredients and components of processed food. Next to genetic or protein markers, chemicals are unique identifiers of food components. Non-targeted metabolomics is ideally suited to...

Anticancer Drug Affects Metabolomic Profiles in Multicellular Spheroids: Studies Using Mass Spectrometry Imaging Combined with Machine Learning.

Analytical chemistry
Multicellular spheroids (hereinafter referred to as spheroids) are 3D biological models. The metabolomic profiles inside spheroids provide crucial information reflecting the molecular phenotypes and microenvironment of cells. To study the influence o...

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics.

Analytical chemistry
Recent developments in high-resolution mass spectrometry (HRMS) technology enabled ultrasensitive detection of proteins, peptides, and metabolites in limited amounts of samples, even single cells. However, extraction of trace-abundance signals from c...