AIMC Topic: Tandem Mass Spectrometry
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Predicting the Predicted: A Comparison of Machine Learning-Based Collision Cross-Section Prediction Models for Small Molecules.
Analytical chemistry
May 24, 2024
The application of machine learning (ML) to -omics research is growing at an exponential rate owing to the increasing availability of large amounts of data for model training. Specifically, in metabolomics, ML has enabled the prediction of tandem mas...
Determination of Patulin in Apple Juice and Apple-Derived Products Using a Robotic Sample Preparation System and LC-APCI-MS/MS.
Toxins
May 23, 2024
Patulin, a toxic mycotoxin, can contaminate apple-derived products. The FDA has established an action level of 50 ppb (ng/g) for patulin in apple juice and apple juice products. To effectively monitor this mycotoxin, there is a need for adequate anal...
Systematic Assessment of Deep Learning-Based Predictors of Fragmentation Intensity Profiles.
Journal of proteome research
May 10, 2024
In recent years, several deep learning-based methods have been proposed for predicting peptide fragment intensities. This study aims to provide a comprehensive assessment of six such methods, namely Prosit, DeepMass:Prism, pDeep3, AlphaPeptDeep, Pros...
Fragment ion intensity prediction improves the identification rate of non-tryptic peptides in timsTOF.
Nature communications
May 10, 2024
Immunopeptidomics is crucial for immunotherapy and vaccine development. Because the generation of immunopeptides from their parent proteins does not adhere to clear-cut rules, rather than being able to use known digestion patterns, every possible pro...
Prediction of quality markers in Maren Runchang pill for constipation using machine learning and network pharmacology.
Molecular omics
May 7, 2024
Maren Runchang pill (MRRCP) is a Chinese patent medicine used to treat constipation in clinics. It has multi-component and multi-target characteristics, and there is an urgent need to screen markers to ensure its quality. The aim of this study was to...
Target Cell Extraction and Spectrum-Effect Relationship Coupled with BP Neural Network Classification for Screening Potential Bioactive Components in Ginseng Extract with a Protective Effect against Myocardial Damage.
Molecules (Basel, Switzerland)
Apr 28, 2024
Cardiovascular disease has become a common ailment that endangers human health, having garnered widespread attention due to its high prevalence, recurrence rate, and sudden death risk. Ginseng possesses functions such as invigorating vital energy, en...
The combination of deep learning and pseudo-MS image improves the applicability of metabolomics to congenital heart defect prenatal screening.
Talanta
Apr 17, 2024
To investigate the metabolic alterations in maternal individuals with fetal congenital heart disease (FCHD), establish the FCHD diagnostic models, and assess the performance of these models, we recruited two batches of pregnant women. By metabolomics...
Prediction of glycopeptide fragment mass spectra by deep learning.
Nature communications
Mar 19, 2024
Deep learning has achieved a notable success in mass spectrometry-based proteomics and is now emerging in glycoproteomics. While various deep learning models can predict fragment mass spectra of peptides with good accuracy, they cannot cope with the ...
Naturally occurring caffeic acid phenethyl ester from chestnut honey-based propolis and virtual screening towards DYRK1A.
Natural product research
Feb 1, 2024
Neurodegenerative diseases (NDDs) are disorders with dysfunction and ongoing loss of neurons, glial cells and the neural networks in the brain and spinal cord. DYRK1A protein was reported to modulate to the cytoskeletal fraction in human and mouse br...
AttnPep: A Self-Attention-Based Deep Learning Method for Peptide Identification in Shotgun Proteomics.
Journal of proteome research
Jan 22, 2024
In shotgun proteomics, the proteome search engine analyzes mass spectra obtained by experiments, and then a peptide-spectra match (PSM) is reported for each spectrum. However, most of the PSMs identified are incorrect, and therefore various postproce...
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