Frontiers | Proteomics Approaches for Biomarker and Drug Target Discovery in ALS and FTD
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Technical comparison of DDA and different types of DIA in a biological... | Download Scientific Diagram
Strategies to enable large-scale proteomics for reproducible research | Nature Communications
DIA mass spectrometry | Nature Methods
Data-independent acquisition mass spectrometry (DIA-MS) for proteomic applications in oncology - Molecular Omics (RSC Publishing) DOI:10.1039/D0MO00072H
IJMS | Free Full-Text | Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis
Benchmarking of analysis strategies for data-independent acquisition proteomics using a large-scale dataset comprising inter-patient heterogeneity | Nature Communications
Data-independent acquisition mass spectrometry (DIA-MS) for proteomic applications in oncology - Molecular Omics (RSC Publishing) DOI:10.1039/D0MO00072H
Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS | Nature Communications
Frontiers | Recent Developments in Data Independent Acquisition (DIA) Mass Spectrometry: Application of Quantitative Analysis of the Brain Proteome
Hybrid Spectral Library Combining DIA-MS Data and a Targeted Virtual Library Substantially Deepens the Proteome Coverage - ScienceDirect
Deep representation features from DreamDIAXMBD improve the analysis of data-independent acquisition proteomics | Communications Biology
A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins | Scientific Data
DIALib-QC an assessment tool for spectral libraries in data-independent acquisition proteomics | Nature Communications
Mass Spectrometry Protocols and Methods | Springer Nature Experiments
Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry | Nature Communications
Group-DIA: analyzing multiple data-independent acquisition mass spectrometry data files | Nature Methods
Streamlined single-cell proteomics by an integrated microfluidic chip and data-independent acquisition mass spectrometry | Nature Communications
Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning | Nature Methods
Generating high quality libraries for DIA MS with empirically corrected peptide predictions | Nature Communications
Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics | Nature Communications
DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics | Nature Methods
MaxDIA enables library-based and library-free data-independent acquisition proteomics | Nature Biotechnology
