AIMC Topic: Tandem Mass Spectrometry
Clear Filters Showing 101 to 110 of 289 articles
Pure Ion Chromatograms Combined with Advanced Machine Learning Methods Improve Accuracy of Discriminant Models in LC-MS-Based Untargeted Metabolomics.
Molecules (Basel, Switzerland)
May 5, 2021
Untargeted metabolomics based on liquid chromatography coupled with mass spectrometry (LC-MS) can detect thousands of features in samples and produce highly complex datasets. The accurate extraction of meaningful features and the building of discrimi...
pDeepXL: MS/MS Spectrum Prediction for Cross-Linked Peptide Pairs by Deep Learning.
Journal of proteome research
Apr 6, 2021
In cross-linking mass spectrometry, the identification of cross-linked peptide pairs heavily relies on the ability of a database search engine to measure the similarities between experimental and theoretical MS/MS spectra. However, the lack of accura...
SteroidXtract: Deep Learning-Based Pattern Recognition Enables Comprehensive and Rapid Extraction of Steroid-Like Metabolic Features for Automated Biology-Driven Metabolomics.
Analytical chemistry
Mar 30, 2021
Despite the vast amount of metabolic information that can be captured in untargeted metabolomics, many biological applications are looking for a biology-driven metabolomics platform that targets a set of metabolites that are relevant to the given bio...
Pharmacokinetics of Eltrombopag in Healthy Chinese Subjects and Effect of Sex and Genetic Polymorphism on its Pharmacokinetic and Pharmacodynamic Variability.
European journal of drug metabolism and pharmacokinetics
Mar 29, 2021
BACKGROUND AND OBJECTIVE: Eltrombopag is the first oral, small-molecule, non-peptide thrombopoietin receptor agonist for the treatment of idiopathic thrombocytopenic purpura. This study investigated the pharmacokinetics of eltrombopag in healthy Chin...
Machine Learning Identifies Metabolic Signatures that Predict the Risk of Recurrent Angina in Remitted Patients after Percutaneous Coronary Intervention: A Multicenter Prospective Cohort Study.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 8, 2021
Recurrent angina (RA) after percutaneous coronary intervention (PCI) has few known risk factors, hampering the identification of high-risk populations. In this multicenter study, plasma samples are collected from patients with stable angina after PCI...
Deep learning the collisional cross sections of the peptide universe from a million experimental values.
Nature communications
Feb 19, 2021
The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate the nature and utility of the peptide collisional cross section (CCS) space, we measure more than a million dat...
Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy.
BMC bioinformatics
Dec 30, 2020
BACKGROUND: Personalized cancer vaccines are emerging as one of the most promising approaches to immunotherapy of advanced cancers. However, only a small proportion of the neoepitopes generated by somatic DNA mutations in cancer cells lead to tumor r...
Simultaneous determination and quantitation of hypolipidemic drugs in fingerprints by UPLC-Q-TRAP/MS.
Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
Dec 16, 2020
An ultra-performance liquid chromatography tandem triple quadrupole compound linear ion trap mass spectrometry (UPLC-Q-TRAP/MS) method was developed and validated for the detection of hypolipidemic drugs in fingerprints. 13 hypolipidemic drugs were w...
Towards compound identification of synthetic opioids in nontargeted screening using machine learning techniques.
Drug testing and analysis
Dec 9, 2020
The constant evolution of the illicit drug market makes the identification of unknown compounds problematic. Obtaining certified reference materials for a broad array of new analogues can be difficult and cost prohibitive. Machine learning provides a...
Deep learning embedder method and tool for mass spectra similarity search.
Journal of proteomics
Dec 8, 2020
Spectral similarity calculation is widely used in protein identification tools and mass spectra clustering algorithms while comparing theoretical or experimental spectra. The performance of the spectral similarity calculation plays an important role ...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32021
- Neural Networks, Computer 30231
- Algorithms 27405
- Deep Learning 26912
- Artificial Intelligence 24844
- Robotics 13389
- Image Processing, Computer-Assisted 9738
- Retrospective Studies 9346
- Magnetic Resonance Imaging 6347
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4866
- Support Vector Machine 4771
- Computational Biology 4333
- Brain 4129
- Computer Simulation 3935
Recent Journals
- Scientific reports 6800
- Sensors (Basel, Switzerland) 4794
- PloS one 4210
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1172
- Journal of chemical information and modeling 1066
- Nature communications 1047
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 874
- Journal of medical Internet research 864
- Briefings in bioinformatics 853