Metabolomics and Mass Spectrometry Studies

IsoSolve: an integrative framework to improve isotopic coverage and consolidate isotopic measurements by MS and/or NMR

IsoSolve integrates isotopic measurements from MS and NMR to improve isotopic coverage and consolidate data for metabolic network analysis.

Spatial single-cell profiling of intracellular metabolomes in situ

SpaceM integrates MALDI-imaging mass spectrometry with pre- and post-MALDI microscopy to measure >100 metabolites in >10000 individual cultured cells alongside fluorescence, morphology and spatial context.

Ion Identity Molecular Networking in the GNPS Environment

The paper introduces Ion Identity Molecular Networking to connect ion species of the same molecule, improving network connectivity and annotation.

Leveraging the mass balances of cellular metabolism to infer absolute concentrations from relative abundance metabolomics data

The paper introduces MetaboPAC, a computational framework that infers absolute metabolite concentrations from relative abundance data using mass balance and kinetic equations, outperforming existing methods under various conditions.

Retention Time Standardization and Registration (RTStaR): An algorithm that matches corresponding and identifies unique species in nanoliquid chromatography-nanoelectrospray ionization-mass spectrometry lipidomic datasets

RTStaR standardizes and registers lipidomic datasets to match and identify unique lipid species across different matrices and organisms.

An aging clock using metabolomic CSF

This paper develops a metabolomic age prediction model using CSF data from healthy humans and applies it to Alzheimer's and Parkinson's patients, finding increased prediction error in disease cohorts.

Automatic classification of constitutive and non-constitutive metabolites with gcProfileMakeR

gcProfileMakeR automatically classifies constitutive and non-constitutive metabolites from GC-MS data, improving speed and accuracy in non-targeted metabolomics.

Rapid Development of Improved Data-dependent Acquisition Strategies.

This paper develops new data-dependent acquisition strategies for metabolomics using an in silico framework, showing they fragment more unique ions than standard methods.

Analyzing Assay Specificity in Metabolomics using Unique Ion Signature Simulations

The paper evaluates metabolomics assay specificity using simulations and shows DIA outperforms MS1 and MRM in unique compound detection.

HERMES: a molecular formula-oriented method to target the metabolome

HERMES improves metabolite identification and structural annotation in mass spectrometry by using molecular formulas and avoiding peak detection.

Metabolic changes in brain slices over time: a multiplatform metabolomics approach

This study uses multiplatform metabolomics to identify metabolic changes in brain slices over time, revealing 300 compound modifications related to lipid classes, GABAergic pathway, and TCA cycle.

SIMILE enables alignment of fragmentation mass spectra with statistical significance

SIMILE aligns fragmentation mass spectra with statistical significance, identifying more structurally similar compound pairs than cosine-based methods.

Expanding the Coverage of the Metabolic Landscape in Cultivated Rice with Integrated Computational Approaches

The paper expands metabolite annotation coverage in rice using integrated computational approaches and reveals differential flavonoid accumulation between indica and japonica cultivars.

Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships

Spec2Vec improves spectral similarity scoring by learning fragmental relationships, showing better correlation with structural similarity than cosine-based scores in metabolomics analyses.

Estimation of permutation-based metabolome-wide significance thresholds

The paper estimates permutation-based metabolome-wide significance thresholds using parametric approximations and permutation procedures to control type I error rates in metabolome-wide association studies.

Joint automatic metabolite identification and quantification of a set of 1H NMR spectra

This paper introduces a method for joint metabolite identification and quantification across multiple 1H NMR spectra, improving accuracy, especially at low concentrations.

Human Tear Metabolomics Using Liquid Chromatography-Q Exactive-HF Mass Spectrometry

This study identifies and characterizes human tear metabolites using untargeted mass spectrometry, finding 82 metabolites with 59 novel to healthy tears.

Variational autoencoders learn universal latent representations of metabolomics data

This study trains a variational autoencoder on metabolomics data to learn nonlinear latent representations and validates its generalizability across different disease cohorts.

Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

The paper performs a metabolome-wide association study to identify CSF metabolite-phenotype associations in neurological and psychiatric disorders.

Lilikoi V2.0: a deep-learning enabled, personalized pathway-based R package for diagnosis and prognosis predictions using metabolomics data

Lilikoi V2.0 is a new R package that uses deep learning and machine learning for disease classification and prognosis prediction using metabolomics data.

Precision mapping of the mouse brain metabolome

This study maps the mouse brain metabolome using targeted metabolomics, creating detailed maps of 79 metabolites at high resolution.

Screening for inborn errors of metabolism using untargeted metabolomics and out-of-batch controls

The paper develops a normalization method for untargeted metabolomics data to reduce batch effects and improve detection of metabolic biomarkers using out-of-batch controls.

SmartPeak automates targeted and quantitative metabolomics data processing

SmartPeak automates metabolomics data processing with algorithms for alignment, calibration, and peak integration, improving reproducibility and throughput.

Classes for the masses: Systematic classification of unknowns using fragmentation spectra

CANOPUS is a tool that predicts compound classes from fragmentation spectra, enabling annotation of unknown compounds without reference data.

Chemically-informed Analyses of Metabolomics Mass Spectrometry Data with Qemistree

The paper introduces Qemistree, a method for analyzing metabolomics mass spectrometry data using hierarchical molecular fingerprints and chemical ontologies to explore chemical composition.

Urine metabolomics of rats with chronic atrophic gastritis

This study identifies 68 differential metabolites in urine of rats with chronic atrophic gastritis using LC-MS, highlighting key metabolic pathways involved.

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS.

The paper develops a machine learning workflow for auto-deconvolution of GC-MS data within GNPS, enabling molecular networking and applications in breathomics and volatilome mapping.

Reactomics: Using mass spectrometry as a chemical reaction detector

The paper introduces Reactomics, a method using mass spectrometry to directly retrieve biochemical relationships from untargeted metabolomics data without prior compound identification.

Corna - An Open Source Python Tool For Natural Abundance Correction In Isotope Tracer Experiments

Corna is a Python tool for natural abundance correction in isotope tracer experiments, offering integrated workflows and reducing processing times.

matchms - processing and similarity evaluation of mass spectrometry data

The paper introduces matchms, a tool for processing and evaluating similarity in mass spectrometry data, addressing challenges in dataset consistency and metadata quality.