Data analysis strategies for targeted and untargeted LC-MS metabolomic studies: Overview and workflow
Data analysis is a very challenging task in LC-MS metabolomic studies. The use of powerful
analytical techniques (eg, high-resolution mass spectrometry) provides high-dimensional …
analytical techniques (eg, high-resolution mass spectrometry) provides high-dimensional …
Critical assessment of the chemical space covered by LC–HRMS non-targeted analysis
Non-targeted analysis (NTA) has emerged as a valuable approach for the comprehensive
monitoring of chemicals of emerging concern (CECs) in the exposome. The NTA approach …
monitoring of chemicals of emerging concern (CECs) in the exposome. The NTA approach …
Drift time-specific collision energies enable deep-coverage data-independent acquisition proteomics
We present a data-independent acquisition mass spectrometry method, ultradefinition (UD)
MSE. This approach utilizes ion mobility drift time-specific collision-energy profiles to …
MSE. This approach utilizes ion mobility drift time-specific collision-energy profiles to …
Label-free quantification in ion mobility–enhanced data-independent acquisition proteomics
Unbiased data-independent acquisition (DIA) strategies have gained increased popularity in
the field of quantitative proteomics. The integration of ion mobility separation (IMS) into DIA …
the field of quantitative proteomics. The integration of ion mobility separation (IMS) into DIA …
xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data
Background Detection of low abundance metabolites is important for de novo map** of
metabolic pathways related to diet, microbiome or environmental exposures. Multiple …
metabolic pathways related to diet, microbiome or environmental exposures. Multiple …
Improved peptide retention time prediction in liquid chromatography through deep learning
C Ma, Y Ren, J Yang, Z Ren, H Yang, S Liu - Analytical chemistry, 2018 - ACS Publications
The accuracy of peptide retention time (RT) prediction model in liquid chromatography (LC)
is still not sufficient for wider implementation in proteomics practice. Herein, we propose …
is still not sufficient for wider implementation in proteomics practice. Herein, we propose …
Interacting quantum atoms—a review
The aim of this review is threefold. On the one hand, we intend it to serve as a gentle
introduction to the Interacting Quantum Atoms (IQA) methodology for those unfamiliar with it …
introduction to the Interacting Quantum Atoms (IQA) methodology for those unfamiliar with it …
Computational methods for understanding mass spectrometry–based shotgun proteomics data
Computational proteomics is the data science concerned with the identification and
quantification of proteins from high-throughput data and the biological interpretation of their …
quantification of proteins from high-throughput data and the biological interpretation of their …
Comparative mass spectrometry-based metabolomics strategies for the investigation of microbial secondary metabolites
Covering: 2000 to 2016 The labor-intensive process of microbial natural product discovery is
contingent upon identifying discrete secondary metabolites of interest within complex …
contingent upon identifying discrete secondary metabolites of interest within complex …
Algorithms and tools for the preprocessing of LC–MS metabolomics data
Metabolomics encompasses the study of small molecules in a biological sample. Liquid
Chromatography coupled with Mass Spectrometry (LC–MS) profiling is an important …
Chromatography coupled with Mass Spectrometry (LC–MS) profiling is an important …