AIMC Topic: Tandem Mass Spectrometry
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Free amino acids in African indigenous vegetables: Analysis with improved hydrophilic interaction ultra-high performance liquid chromatography tandem mass spectrometry and interactive machine learning.
Journal of chromatography. A
Dec 5, 2020
A hydrophilic interaction (HILIC) ultra-high performance liquid chromatography (UHPLC) with triple quadrupole tandem mass spectrometry (MS/MS) method was developed and validated for the quantification of 21 free amino acids (AAs). Compared to publish...
Development of LC-MS/MS determination method and backpropagation artificial neural networks pharmacokinetic model of febuxostat in healthy subjects.
Journal of clinical pharmacy and therapeutics
Nov 17, 2020
WHAT IS KNOWN AND OBJECTIVE: Febuxostat is a well-known drug for treating hyperuricemia and gout. The published methods for determination of febuxostat in human plasma might be unsuitable for high-throughput determination and widespread application. ...
Deep Learning in Proteomics.
Proteomics
Oct 30, 2020
Proteomics, the study of all the proteins in biological systems, is becoming a data-rich science. Protein sequences and structures are comprehensively catalogued in online databases. With recent advancements in tandem mass spectrometry (MS) technolog...
DeepRescore: Leveraging Deep Learning to Improve Peptide Identification in Immunopeptidomics.
Proteomics
Sep 27, 2020
The identification of major histocompatibility complex (MHC)-binding peptides in mass spectrometry (MS)-based immunopeptideomics relies largely on database search engines developed for proteomics data analysis. However, because immunopeptidomics expe...
An Approach to Biomarker Discovery of Cannabis Use Utilizing Proteomic, Metabolomic, and Lipidomic Analyses.
Cannabis and cannabinoid research
Jun 19, 2020
Relatively little is known about the molecular pathways influenced by cannabis use in humans. We used a multi-omics approach to examine protein, metabolomic, and lipid markers in plasma differentiating between cannabis users and nonusers to understa...
MealTime-MS: A Machine Learning-Guided Real-Time Mass Spectrometry Analysis for Protein Identification and Efficient Dynamic Exclusion.
Journal of the American Society for Mass Spectrometry
Jun 17, 2020
Mass spectrometry-based proteomics technologies are prime methods for the high-throughput identification of proteins in complex biological samples. Nevertheless, there are still technical limitations that hinder the ability of mass spectrometry to id...
Artificial intelligence and network pharmacology based investigation of pharmacological mechanism and substance basis of Xiaokewan in treating diabetes.
Pharmacological research
May 25, 2020
Xiaokewan is a typical Traditional Chinese medicine (TCM) for diabetes and contains various natural chemicals, such as lignans, flavonoids, saponins, polysaccharides, and western medicine glibenclamide. In the current study, a highly efficient system...
Disease Models, Animal
Drugs, Chinese Herbal
Workflow
Zebrafish
Chromatography, High Pressure Liquid
Tandem Mass Spectrometry
Rats, Wistar
Hypoglycemic Agents
Diabetes Mellitus
Protein Interaction Maps
Animals
Artificial Intelligence
Gene Regulatory Networks
Male
Biomarkers
Data Mining
Systems Biology
Blood Glucose
Spectrometry, Mass, Electrospray Ionization
Animals, Genetically Modified
Retip: Retention Time Prediction for Compound Annotation in Untargeted Metabolomics.
Analytical chemistry
May 21, 2020
Unidentified peaks remain a major problem in untargeted metabolomics by LC-MS/MS. Confidence in peak annotations increases by combining MS/MS matching and retention time. We here show how retention times can be predicted from molecular structures. Tw...
Enhancing Top-Down Proteomics Data Analysis by Combining Deconvolution Results through a Machine Learning Strategy.
Journal of the American Society for Mass Spectrometry
Apr 8, 2020
Top-down mass spectrometry (MS) is a powerful tool for the identification and comprehensive characterization of proteoforms arising from alternative splicing, sequence variation, and post-translational modifications. However, the complex data set gen...
Full-Spectrum Prediction of Peptides Tandem Mass Spectra using Deep Neural Network.
Analytical chemistry
Feb 25, 2020
The ability to predict tandem mass (MS/MS) spectra from peptide sequences can significantly enhance our understanding of the peptide fragmentation process and could improve peptide identification in proteomics. However, current approaches for predict...
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