AIMC Topic: Tandem Mass Spectrometry

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MIST-CF: Chemical Formula Inference from Tandem Mass Spectra.

Journal of chemical information and modeling Sep 19, 2023
Chemical formula annotation for tandem mass spectrometry (MS/MS) data is the first step toward structurally elucidating unknown metabolites. While great strides have been made toward solving this problem, the current state-of-the-art method depends o...
Databases, Factual Tandem Mass Spectrometry Neural Networks, Computer
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MSBooster: improving peptide identification rates using deep learning-based features.

Nature communications Jul 27, 2023
Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFrag...
Peptides Deep Learning Algorithms Tandem Mass Spectrometry Chromatography, Liquid Databases, Protein
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DbyDeep: Exploration of MS-Detectable Peptides via Deep Learning.

Analytical chemistry Jul 17, 2023
Predicting peptide detectability is useful in a variety of mass spectrometry (MS)-based proteomics applications, particularly targeted proteomics. However, most machine learning-based computational methods have relied solely on information from the p...
Peptides Amino Acid Sequence Tandem Mass Spectrometry Deep Learning Proteins
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Microextraction by packed sorbent of N-nitrosamines from Losartan tablets using a high-throughput robot platform followed by liquid chromatography-tandem mass spectrometry.

Journal of separation science Jul 3, 2023
The development of a fast, cost-effective, and efficient microextraction by packed sorbent setup was achieved by combining affordable laboratory-repackable devices of microextraction with a high-throughput cartesian robot. This setup was evaluated fo...
Solid Phase Microextraction Nitrosamines Chromatography, High Pressure Liquid Chromatography, Liquid Tandem Mass Spectrometry Limit of Detection Robotics Tablets Losartan
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Fast screening and identification of illegal adulteration in dietary supplements and herbal medicines using molecular networking with deep-learning-based similarity algorithms.

Analytical and bioanalytical chemistry Apr 29, 2023
Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is a powerful analytical tool used for adulteration inspection. Nevertheless, it is a challenging task to identify illegal adulterants that are not included in the library or are unexp...
Plants, Medicinal Deep Learning Plant Extracts Dietary Supplements Tandem Mass Spectrometry Algorithms
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DeepDetect: Deep Learning of Peptide Detectability Enhanced by Peptide Digestibility and Its Application to DIA Library Reduction.

Analytical chemistry Mar 12, 2023
In tandem mass spectrometry-based proteomics, proteins are digested into peptides by specific protease(s), but generally only a fraction of peptides can be detected. To characterize detectable proteotypic peptides, we have developed a series of metho...
Peptide Hydrolases Tandem Mass Spectrometry Saccharomyces cerevisiae Humans Peptide Library Deep Learning Animals Escherichia coli Proteome Mice Peptides Proteins
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An Interpretable Deep Learning Approach for Biomarker Detection in LC-MS Proteomics Data.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2023
Analyzing mass spectrometry-based proteomics data with deep learning (DL) approaches poses several challenges due to the high dimensionality, low sample size, and high level of noise. Additionally, DL-based workflows are often hindered to be integrat...
Proteomics Chromatography, Liquid Tandem Mass Spectrometry Biomarkers Deep Learning
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Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics.

PLoS computational biology Jan 20, 2023
Generating and analyzing overlapping peptides through multienzymatic digestion is an efficient procedure for de novo protein using from bottom-up mass spectrometry (MS). Despite improved instrumentation and software, de novo MS data analysis remains ...
Antibodies, Monoclonal Deep Learning Peptide Hydrolases Tandem Mass Spectrometry Proteomics Sequence Analysis, Protein Peptides
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Fusion of Quality Evaluation Metrics and Convolutional Neural Network Representations for ROI Filtering in LC-MS.

Analytical chemistry Jan 4, 2023
Region of interest (ROI) extraction is a fundamental step in analyzing metabolomic datasets acquired by liquid chromatography-mass spectrometry (LC-MS). However, noises and backgrounds in LC-MS data often affect the quality of extracted ROIs. Therefo...
Chromatography, Liquid Neural Networks, Computer Tandem Mass Spectrometry Gas Chromatography-Mass Spectrometry Algorithms
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Improving SWATH-MS analysis by deep-learning.

Proteomics Jan 3, 2023
Data-independent acquisition (DIA) of tandem mass spectrometry spectra has emerged as a promising technology to improve coverage and quantification of proteins in complex mixtures. The success of DIA experiments is dependent on the quality of spectra...
Proteins Tandem Mass Spectrometry Databases, Factual Algorithms Deep Learning
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