AIMC Topic: Tandem Mass Spectrometry

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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...
Peptides Deep Learning Databases, Protein Tandem Mass Spectrometry Humans Algorithms Reproducibility of Results
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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...
Substance Abuse Detection Chromatography, Liquid Tandem Mass Spectrometry Cannabinoid Receptor Agonists Adult Humans Hallucinogens Lipids Cannabis Male Lipidomics Biomarkers Analgesics Proteomics Dronabinol Female
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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...
Supervised Machine Learning Tandem Mass Spectrometry HEK293 Cells Algorithms Proteomics Proteins Humans
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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...
Spectrometry, Mass, Electrospray Ionization Animals, Genetically Modified Chromatography, High Pressure Liquid Tandem Mass Spectrometry Data Mining Hypoglycemic Agents Diabetes Mellitus Disease Models, Animal Drugs, Chinese Herbal Workflow Zebrafish Gene Regulatory Networks Systems Biology Rats, Wistar Male Artificial Intelligence Blood Glucose Biomarkers Protein Interaction Maps Animals
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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...
Time Factors Organic Chemicals Metabolomics Chromatography, Liquid Tandem Mass Spectrometry Humans Machine Learning
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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...
Humans Sensitivity and Specificity Proteomics Protein Processing, Post-Translational Machine Learning Data Analysis Algorithms Muscle Proteins Tandem Mass Spectrometry Alternative Splicing Sarcomeres
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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...
Neural Networks, Computer Peptides Tandem Mass Spectrometry
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Untargeted Metabolomics for Metabolic Diagnostic Screening with Automated Data Interpretation Using a Knowledge-Based Algorithm.

International journal of molecular sciences Feb 1, 2020
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...
Tandem Mass Spectrometry Humans Knowledge Bases Metabolism, Inborn Errors Algorithms Mass Screening Biomarkers Metabolome Case-Control Studies Data Interpretation, Statistical
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Machine Learning Classifies Core and Outer Fucosylation of N-Glycoproteins Using Mass Spectrometry.

Scientific reports Jan 15, 2020
Protein glycosylation is known to be involved in biological progresses such as cell recognition, growth, differentiation, and apoptosis. Fucosylation of glycoproteins plays an important role for structural stability and function of N-linked glycoprot...
Fucose Humans Tandem Mass Spectrometry Machine Learning Immunoglobulin gamma-Chains Carbohydrate Sequence Glycosylation Glycopeptides Amino Acid Sequence Chromatography, High Pressure Liquid
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Robotic automation of a UHPLC/MS-MS method profiling one-carbon metabolites, amino acids, and precursors in plasma.

Analytical biochemistry Jan 3, 2020
Amino acids (AAs) and one-carbon (1-C) metabolism compounds are involved in a range of key metabolic pathways, and mediate numerous health and disease processes in the human body. Previous assays have quantified a limited selection of these compounds...
Chromatography, High Pressure Liquid Tandem Mass Spectrometry Automation, Laboratory Robotics Amino Acids Humans
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