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Artificial intelligence in molecular medicine
Artificial Intelligence in Molecular Medicine | New England Journal of Medicine Skip to main
content The New England Journal of Medicine homepage Advanced Search SEARCH …
content The New England Journal of Medicine homepage Advanced Search SEARCH …
Artificial intelligence for proteomics and biomarker discovery
There is an avalanche of biomedical data generation and a parallel expansion in
computational capabilities to analyze and make sense of these data. Starting with genome …
computational capabilities to analyze and make sense of these data. Starting with genome …
Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform
Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass
spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we …
spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we …
MSBooster: improving peptide identification rates using deep learning-based features
Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS)
experiments relies on computational algorithms for matching acquired MS/MS spectra …
experiments relies on computational algorithms for matching acquired MS/MS spectra …
AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics
Abstract Machine learning and in particular deep learning (DL) are increasingly important in
mass spectrometry (MS)-based proteomics. Recent DL models can predict the retention …
mass spectrometry (MS)-based proteomics. Recent DL models can predict the retention …
Data‐independent acquisition mass spectrometry‐based proteomics and software tools: a glimpse in 2020
This review provides a brief overview of the development of data‐independent acquisition
(DIA) mass spectrometry‐based proteomics and selected DIA data analysis tools. Various …
(DIA) mass spectrometry‐based proteomics and selected DIA data analysis tools. Various …
Prediction of peptide mass spectral libraries with machine learning
The recent development of machine learning methods to identify peptides in complex mass
spectrometric data constitutes a major breakthrough in proteomics. Longstanding methods …
spectrometric data constitutes a major breakthrough in proteomics. Longstanding methods …
[HTML][HTML] Acquisition and analysis of DIA-based proteomic data: A comprehensive survey in 2023
R Lou, W Shui - Molecular & Cellular Proteomics, 2024 - Elsevier
Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful
technology for high-throughput, accurate, and reproducible quantitative proteomics. This …
technology for high-throughput, accurate, and reproducible quantitative proteomics. This …
Prediction of glycopeptide fragment mass spectra by deep learning
Y Yang, Q Fang - Nature Communications, 2024 - nature.com
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 …
is now emerging in glycoproteomics. While various deep learning models can predict …
Deep learning in proteomics
Proteomics, the study of all the proteins in biological systems, is becoming a data‐rich
science. Protein sequences and structures are comprehensively catalogued in online …
science. Protein sequences and structures are comprehensively catalogued in online …