AIMC Topic: Tandem Mass Spectrometry
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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...
Identification, synthesis, and characterization of an unprecedented N-(2-carboxyethyl) adduct impurity in an injectable ganirelix formulation.
Journal of peptide science : an official publication of the European Peptide Society
Dec 22, 2023
Ganirelix, a peptide-based drug used to treat female infertility, has been in high market demand, which attracted generic formulation. A hitherto unknown impurity of ganirelix was observed in our formulation process, which reached ~0.3% in 6 months a...
Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances.
Analytical chemistry
Dec 4, 2023
The market for illicit drugs has been reshaped by the emergence of more than 1100 new psychoactive substances (NPS) over the past decade, posing a major challenge to the forensic and toxicological laboratories tasked with detecting and identifying th...
Variability analysis of LC-MS experimental factors and their impact on machine learning.
GigaScience
Nov 20, 2023
BACKGROUND: Machine learning (ML) technologies, especially deep learning (DL), have gained increasing attention in predictive mass spectrometry (MS) for enhancing the data-processing pipeline from raw data analysis to end-user predictions and rescori...
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