Data-independent acquisition mass spectrometry (DIA-MS) for proteomic applications in oncology - Molecular Omics (RSC Publishing) DOI:10.1039/D0MO00072H
Machine Learning in Mass Spectrometric Analysis of DIA Data - Xu - - PROTEOMICS - Wiley Online Library
Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility
In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics | Nature Communications
Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines - ScienceDirect
Nature Methods on Twitter: "Avant-garde: a tool for refining DIA-mass spectrometry data. @JaffeLab https://t.co/zIWJ9PUYiz… "
In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics | Nature Communications
Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: a tutorial | Molecular Systems Biology
DDIA: data dependent-independent acquisition proteomics - DDA and DIA in a single LC-MS/MS run | bioRxiv
Hybrid Spectral Library Combining DIA-MS Data and a Targeted Virtual Library Substantially Deepens the Proteome Coverage - ScienceDirect
In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics | Nature Communications
The workflow of DeepNovo-DIA for de novo sequencing of DIA... | Download Scientific Diagram
SWATH analysis - Why an advantage in mass spectrometry?
Mass spectrometry and proteomics
DIA mass spectrometry | Nature Methods
General workflows for processing DIA spectra. (A) Generation of... | Download Scientific Diagram
Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: a tutorial | Molecular Systems Biology
Group-DIA: analyzing multiple data-independent acquisition mass spectrometry data files | Nature Methods
Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry | Nature Communications
CompMS | MS-DIAL
DIA mass spectrometry | Nature Methods
Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning | Nature Methods
