Clinical applications of quantitative proteomics using targeted and untargeted data-independent acquisition techniques

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments

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Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis

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Absolute Quantification of Proteins by LCMSE

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Selected reaction monitoring–based proteomics: workflows, potential, pitfalls and future directions

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Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues

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MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments

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OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data

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DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics

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Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry

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Targeted Peptide Measurements in Biology and Medicine: Best Practices for Mass Spectrometry-based Assay Development Using a Fit-for-Purpose Approach

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Targeted Proteomic Quantification on Quadrupole-Orbitrap Mass Spectrometer

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Quantitative analysis of peptides and proteins in biomedicine by targeted mass spectrometry

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A repository of assays to quantify 10,000 human proteins by SWATH-MS

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A multicenter study benchmarks software tools for label-free proteome quantification

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Quantitative variability of 342 plasma proteins in a human twin population

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Mapping differential interactomes by affinity purification coupled with data-independent mass spectrometry acquisition

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Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system

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Human SRMAtlas: A Resource of Targeted Assays to Quantify the Complete Human Proteome

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Precursor Acquisition Independent From Ion Count: How to Dive Deeper into the Proteomics Ocean

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Reproducible Quantification of Cancer-Associated Proteins in Body Fluids Using Targeted Proteomics

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Mass spectrometry based biomarker discovery, verification, and validation — Quality assurance and control of protein biomarker assays

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Building ProteomeTools based on a complete synthetic human proteome

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Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma

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Panorama: A Targeted Proteomics Knowledge Base

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Multiplexed peptide analysis using data-independent acquisition and Skyline

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Using data‐independent, high‐resolution mass spectrometry in protein biomarker research: Perspectives and clinical applications

Sajic, T., Liu, Y., & Aebersold, R. H. (2014) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201400117 · Cited by 209 · see citing works

Quantitative measurements of <i><scp>N</scp></i>‐linked glycoproteins in human plasma by <scp>SWATH</scp>‐<scp>MS</scp>

Liu, Y., Hüttenhain, R., Surinova, S., Gillet, L. C., Mouritsen, J., Brunner, R., Navarro, P., & Aebersold, R. (2013) · PROTEOMICS · doi:10.1002/pmic.201200417 · Cited by 204 · see citing works

Technical considerations for large-scale parallel reaction monitoring analysis

Gallien, S., Bourmaud, A., Kim, S.-Y., & Domon, B. (2013) · Journal of Proteomics · doi:10.1016/j.jprot.2013.10.029 · Cited by 198 · see citing works

The Use of Variable Q1 Isolation Windows Improves Selectivity in LC–SWATH–MS Acquisition

Zhang, Y., Pena, A. B., Bruderer, T., Luban, J., Strambio‐De‐Castillia, C., Lisacek, F., Gérard Hopfgartner, D., & Varesio, E. (2015) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00543 · Cited by 193 · see citing works

Processing strategies and software solutions for data‐independent acquisition in mass spectrometry

Pena, A. B., Varesio, E., Luban, J., Strambio‐De‐Castillia, C., Gérard Hopfgartner, D., Müller, M., & Lisacek, F. (2014) · PROTEOMICS · doi:10.1002/pmic.201400323 · Cited by 193 · see citing works

Glycoproteomic Analysis of Prostate Cancer Tissues by SWATH Mass Spectrometry Discovers N-acylethanolamine Acid Amidase and Protein Tyrosine Kinase 7 as Signatures for Tumor Aggressiveness

Liu, Y., Chen, J., Sethi, A., Li, Q. K., Chen, L., Collins, B. C., Gillet, L. C. J., Wollscheid, B., Zhang, H., & Aebersold, R. H. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.038273 · Cited by 187 · see citing works

Peptide-Centric Proteome Analysis: An Alternative Strategy for the Analysis of Tandem Mass Spectrometry Data

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Reproducible and Consistent Quantification of the Saccharomyces cerevisiae Proteome by SWATH-mass spectrometry *

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TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics

Röst, H. L., Liu, Y., D’Agostino, G. A., Zanella, M., Navarro, P., Rosenberger, G., Collins, B. C., Gillet, L. C. J., Testa, G., Malmström, L., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3954 · Cited by 163 · see citing works

mapDIA: Preprocessing and statistical analysis of quantitative proteomics data from data independent acquisition mass spectrometry

Teo, G., Kim, S., Tsou, C., Collins, B. C., Gingras, A., Nesvizhskii, A. I., & Choi, H. (2015) · Journal of Proteomics · doi:10.1016/j.jprot.2015.09.013 · Cited by 145 · see citing works

Advances in multiplexed MRM-based protein biomarker quantitation toward clinical utility

Percy, A. J., Chambers, A. G., Yang, J., Hardie, D. B., & Borchers, C. H. (2013) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2013.06.008 · Cited by 145 · see citing works

Large‐scale multiplex absolute protein quantification of drug‐metabolizing enzymes and transporters in human intestine, liver, and kidney microsomes by SWATH‐MS: Comparison with MRM/SRM and HR‐MRM/PRM

Nakamura, K., Hirayama‐Kurogi, M., Ito, S., Kuno, T., Yoneyama, T., Obuchi, W., Terasaki, T., & Ohtsuki, S. (2016) · PROTEOMICS · doi:10.1002/pmic.201500433 · Cited by 136 · see citing works

Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer

Muntel, J., Xuan, Y., Berger, S. T., Reiter, L., Bachur, R. G., Kentsis, A., & Steen, H. (2015) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00826 · Cited by 135 · see citing works

MSPLIT-DIA: sensitive peptide identification for data-independent acquisition

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Design, Implementation and Multisite Evaluation of a System Suitability Protocol for the Quantitative Assessment of Instrument Performance in Liquid Chromatography-Multiple Reaction Monitoring-MS (LC-MRM-MS)

Abbatiello, S. E., Mani, D. R., Schilling, B., MacLean, B., Zimmerman, L. J., Feng, X., Cusack, M. P., Sedransk, N., Hall, S. C., Addona, T. A., et al. (2013) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m112.027078 · Cited by 113 · see citing works

Multiplexed, Scheduled, High-Resolution Parallel Reaction Monitoring on a Full Scan QqTOF Instrument with Integrated Data-Dependent and Targeted Mass Spectrometric Workflows

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Method of the Year 2012

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Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH) Analysis for Characterization and Quantification of Histone Post-translational Modifications

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Group-DIA: analyzing multiple data-independent acquisition mass spectrometry data files

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XDIA: improving on the label-free data-independent analysis

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Identification of a Set of Conserved Eukaryotic Internal Retention Time Standards for Data-independent Acquisition Mass Spectrometry

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Generation of High-Quality SWATH® Acquisition Data for Label-free Quantitative Proteomics Studies Using TripleTOF® Mass Spectrometers

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Discovery of potential protein biomarkers of lung adenocarcinoma in bronchoalveolar lavage fluid by SWATH MS data-independent acquisition and targeted data extraction

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Precise label-free quantitative proteomes in high-throughput by microLC and data-independent SWATH acquisition

Vowinckel, J., Zelezniak, A., Kibler, A., Bruderer, R., Muelleder, M., Reiter, L., & Ralser, M. (2016) · doi:10.1101/073478 · Cited by 81 · see citing works

Quantification of lysine acetylation and succinylation stoichiometry in proteins using mass spectrometric data-independent acquisitions (SWATH)

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Cost-effective generation of precise label-free quantitative proteomes in high-throughput by microLC and data-independent acquisition

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Using the CPTAC Assay Portal to Identify and Implement Highly Characterized Targeted Proteomics Assays

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Quantitative Proteomics by SWATH-MS Reveals Altered Expression of Nucleic Acid Binding and Regulatory Proteins in HIV-1-Infected Macrophages

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Untargeted, spectral library‐free analysis of data‐independent acquisition proteomics data generated using Orbitrap mass spectrometers

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Evaluation of proteomic biomarkers associated with circulating microparticles as an effective means to stratify the risk of spontaneous preterm birth

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Applications and Developments in Targeted Proteomics: From SRM to DIA/SWATH

Aebersold, R. H., Bensimon, A., Collins, B. C., Ludwig, C., & Sabidó, E. (2016) · PROTEOMICS · doi:10.1002/pmic.201600203 · Cited by 71 · see citing works

Quantification of SAHA-Dependent Changes in Histone Modifications Using Data-Independent Acquisition Mass Spectrometry

Krautkramer, K. A., Reiter, L., Denu, J. M., & Dowell, J. A. (2015) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00245 · Cited by 70 · see citing works

An Automated Pipeline to Monitor System Performance in Liquid Chromatography–Tandem Mass Spectrometry Proteomic Experiments

Bereman, M. S., Beri, J., Sharma, V., Nathe, C., Eckels, J., MacLean, B., & MacCoss, M. J. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6b00744 · Cited by 69 · see citing works

Detection and quantification of proteins in clinical samples using high resolution mass spectrometry

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Building the Connectivity Map of epigenetics: Chromatin profiling by quantitative targeted mass spectrometry

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Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometryPreprint

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SWATH analysis of the synaptic proteome in Alzheimer's disease

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Understanding the dimorphic lifestyles of human gastric pathogen Helicobacter pylori using the SWATH-based proteomics approach

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Assessment of SRM, MRM3, and DIA for the targeted analysis of phosphorylation dynamics in non‐small cell lung cancer

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Minimal sample requirement for highly multiplexed protein quantification in cell lines and tissues by PCT‐SWATH mass spectrometry

Shao, S., Guo, T., Koh, C. C., Gillessen, S., Joerger, M., Jochum, W., & Aebersold, R. H. (2015) · PROTEOMICS · doi:10.1002/pmic.201500161 · Cited by 48 · see citing works

Biomarker Discovery and Verification of Esophageal Squamous Cell Carcinoma Using Integration of SWATH/MRM

Hou, G., Lou, X., Sun, Y., Xu, S., Zi, J., Wang, Q., Zhou, B., Han, B. H., Wu, L., Zhao, X., et al. (2015) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00438 · Cited by 48 · see citing works

Clinical translation of MS-based, quantitative plasma proteomics: status, challenges, requirements, and potential

Percy, A. J., Byrns, S., Pennington, S. R., Holmes, D. T., Anderson, N. L., Agreste, T. M., & Duffy, M. A. (2016) · Expert Review of Proteomics · doi:10.1080/14789450.2016.1205950 · Cited by 47 · see citing works

Targeted proteomics coming of age – SRM, PRM and DIA performance evaluated from a core facility perspective

Kockmann, T., Trachsel, C., Panse, C., Wåhlander, Å., Selevsek, N., Grossmann, J., Wolski, W., & Schlapbach, R. (2016) · PROTEOMICS · doi:10.1002/pmic.201500502 · Cited by 43 · see citing works

Opening a SWATH Window on Posttranslational Modifications: Automated Pursuit of Modified Peptides

Keller, A., Bader, S. L., Kusebauch, U., Shteynberg, D. D., Hood, L., & Moritz, R. L. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m115.054478 · Cited by 39 · see citing works

Tools for monitoring system suitability in LC MS/MS centric proteomic experiments

Bereman, M. S. (2014) · PROTEOMICS · doi:10.1002/pmic.201400373 · Cited by 36 · see citing works

A framework for installable external tools in Skyline

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Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

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Quantitative proteogenomics of human pathogens using DIA-MS

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Variation and quantification among a target set of phosphopeptides in human plasma by multiple reaction monitoring and SWATH‐MS2 data‐independent acquisition

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Mass Spectral Enhanced Detection of Ubls Using SWATH Acquisition: MEDUSA—Simultaneous Quantification of SUMO and Ubiquitin-Derived Isopeptides

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Rapid label‐free profiling of oral cancer biomarker proteins using nano‐UPLC‐Q‐TOF ion mobility mass spectrometry

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Applying SWATH Mass Spectrometry to Investigate Human Cervicovaginal Fluid During the Menstrual Cycle1

Vaswani, K., Ashman, K., Reed, S., Salomón, C., Sarker, S., Arraztoa, J. A., Pérez‐Sepúlveda, A., Illanes, S. E., Kvaskoff, D., Mitchell, M. D., et al. (2015) · Biology of Reproduction · doi:10.1095/biolreprod.115.128231 · Cited by 17 · see citing works

A reference library of peripheral blood mononuclear cells for SWATH‐MS analysis

Silva, C. S., Santa, C., Anjo, S. I., & Manadas, B. J. (2016) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201600070 · Cited by 16 · see citing works

Multiple Biomarker Panels for Early Detection of Breast Cancer in Peripheral Blood

Zhang, F., Deng, Y., & Drabier, R. (2013) · BioMed Research International · doi:10.1155/2013/781618 · Cited by 12 · see citing works

Quantifying the human proteome

Paulovich, A. G., & Whiteaker, J. R. (2016) · Nature Biotechnology · doi:10.1038/nbt.3695 · Cited by 9 · see citing works

p-SRM, SWATH and HRM – Targeted Proteomics Approaches on TripleTOF 5600+ Mass Spectrometer and Th eir Applications in Oncology Research

Faktor, J., Michalová, E., & Bouchal, P. (2014) · Klinicka onkologie · doi:10.14735/amko20141s110 · Cited by 4 · see citing works

Peptides aplenty

Doerr, A. J. (2013) · Nature Methods · doi:10.1038/nmeth.2548 · Cited by 2 · see citing works

The Mitochondrial Acylome Emerges: Proteomics, Regulation by Sirtuins, and Metabolic and Disease Implications

Carrico, C., Meyer, J. G., He, W., Gibson, B. W., & Verdin, E. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.01.016 · Cited by 331 · see citing works

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

Macklin, A. M., Khan, S., & Kislinger, T. (2020) · Clinical Proteomics · doi:10.1186/s12014-020-09283-w · Cited by 320 · see citing works

Understanding interactions between biomaterials and biological systems using proteomics

Othman, Z., Cillero‐Pastor, B., van Rijt, S., & Habibović, P. (2018) · Biomaterials · doi:10.1016/j.biomaterials.2018.03.020 · Cited by 203 · see citing works

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

Jiang, Y., Balaya, R. D. A., Schuster, D., Neely, B. A., Rosano, G. L., Volkmar, N., Momenzadeh, A., Peters-Clarke, T. M., Egbert, S., Kreimer, S. D., et al. (2024) · ACS Measurement Science Au · doi:10.1021/acsmeasuresciau.3c00068 · Cited by 200 · see citing works

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

Manes, N. P., & Nita‐Lazar, A. (2018) · Journal of Proteomics · doi:10.1016/j.jprot.2018.02.008 · Cited by 124 · see citing works

Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau

Rayaprolu, S., Higginbotham, L., Bagchi, P., Watson, C. M., Zhang, T., Levey, A. I., Rangaraju, S., & Seyfried, N. T. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-020-00840-3 · Cited by 118 · see citing works

Deep learning neural network tools for proteomics

Meyer, J. G. (2021) · Cell Reports Methods · doi:10.1016/j.crmeth.2021.100003 · Cited by 95 · see citing works

DPHL: A DIA Pan-Human Protein Mass Spectrometry Library for Robust Biomarker Discovery

Zhu, T., Zhu, Y., Xuan, Y., Gao, H., Cai, X., Piersma, S. R., Pham, T. V., Schelfhorst, T., de Haas, R. R., Bijnsdorp, I. V., et al. (2020) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2019.11.008 · Cited by 94 · see citing works

Mass spectrometry‐based tear proteomics for noninvasive biomarker discovery

Ponzini, E., Santambrogio, C., Palma, A. D., Mauri, P., Tavazzi, S., & Grandori, R. (2021) · Mass Spectrometry Reviews · doi:10.1002/mas.21691 · Cited by 93 · see citing works

Proteomic Biomarkers for the Detection of Endometrial Cancer

Njoku, K., Chiasserini, D., Whetton, A. D., & Crosbie, E. J. (2019) · Cancers · doi:10.3390/cancers11101572 · Cited by 87 · see citing works

High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis

Lin, L., Zheng, J., Yu, Q., Chen, W., Xing, J., Chen, C., & Tian, R. (2017) · Journal of Proteomics · doi:10.1016/j.jprot.2017.12.014 · Cited by 84 · see citing works

Quantitative shotgun proteome analysis by direct infusion

Meyer, J. G., Niemi, N. M., Pagliarini, D. J., & Coon, J. J. (2020) · Nature Methods · doi:10.1038/s41592-020-00999-z · Cited by 73 · see citing works

Omics technologies in allergy and asthma research: An EAACI position paper

Radzikowska, U., Baerenfaller, K., Cornejo-García, J. A., Karaaslan, Ç., Barletta, E., Sarac, B. E., Zhakparov, D., Villaseñor, A., Eguíluz‐Gracia, I., Mayorga, C., et al. (2022) · Allergy · doi:10.1111/all.15412 · Cited by 77 · see citing works

The power of proteomics to monitor senescence-associated secretory phenotypes and beyond: toward clinical applications

Basisty, N., Kale, A., Patel, S., Campisi, J., & Schilling, B. (2020) · Expert Review of Proteomics · doi:10.1080/14789450.2020.1766976 · Cited by 69 · see citing works

Mass spectrometry based proteomics and metabolomics in personalized oncology

Kowalczyk, T., Ciborowski, M., Kiśluk, J., Kretowski, A. J., & Barbas, C. (2020) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2020.165690 · Cited by 67 · see citing works

Proteomic investigation on bio-corona of Au, Ag and Fe nanoparticles for the discovery of triple negative breast cancer serum protein biomarkers

Chantada‐Vázquez, M. D. P., López, A. C., García-Vence, M., Vázquez‐Estévez, S., Nebril, B. A., Calatayud, D. G., Jardiel, T., Bravo, S. B., & Núñez, C. (2019) · Journal of Proteomics · doi:10.1016/j.jprot.2019.103581 · Cited by 63 · see citing works

Quantitative Proteomics and Metabolomics Reveal Biomarkers of Disease as Potential Immunotherapy Targets and Indicators of Therapeutic Efficacy

MacMullan, M. A., Dunn, Z. S., Graham, N., Yang, L., & Wang, P. (2019) · Theranostics · doi:10.7150/thno.37373 · Cited by 59 · see citing works

Exosomes in chronic respiratory diseases

Purghè, B., Manfredi, M., Ragnoli, B., Baldanzi, G., & Malerba, M. (2021) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2021.112270 · Cited by 58 · see citing works

Deepening our understanding of HDL proteome

Ronsein, G. E., & Vaisar, T. (2019) · Expert Review of Proteomics · doi:10.1080/14789450.2019.1650645 · Cited by 57 · see citing works

An overview of technologies for MS-based proteomics-centric multi-omics

Rajczewski, A., Jagtap, P., & Griffin, T. J. (2022) · Espert Review of Proteomics · doi:10.1080/14789450.2022.2070476 · Cited by 39 · see citing works

The Role of Data-Independent Acquisition for Glycoproteomics

Ye, Z., & Vakhrushev, S. Y. (2020) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r120.002204 · Cited by 52 · see citing works

MS1 ion current‐based quantitative proteomics: A promising solution for reliable analysis of large biological cohorts

Wang, X., Shen, S., Rasam, S. S., & Qu, J. (2019) · Mass Spectrometry Reviews · doi:10.1002/mas.21595 · Cited by 50 · see citing works

Quantitative SWATH-Based Proteomic Profiling for Identification of Mechanism-Driven Diagnostic Biomarkers Conferring in the Progression of Metastatic Prostate Cancer

Singh, A. N., & Sharma, N. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.00493 · Cited by 47 · see citing works

Circulating proteomic panels for diagnosis and risk stratification of acute-on-chronic liver failure in patients with viral hepatitis B

Sun, Z., Liu, X., Wu, D., Gao, H., Jiang, J., Yang, Y., Wu, J., Gao, Q., Wang, J., Jiang, Z., et al. (2019) · Theranostics · doi:10.7150/thno.31991 · Cited by 47 · see citing works

Peptide Correlation Analysis (PeCorA) Reveals Differential Proteoform Regulation

Dermit, M., Peters-Clarke, T. M., Shishkova, E., & Meyer, J. G. (2021) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00602 · Cited by 40 · see citing works

Optimization of Ultrafast Proteomics Using an LC-Quadrupole-Orbitrap Mass Spectrometer with Data-Independent Acquisition

Ishikawa, M., Konno, R., Nakajima, D., Gotoh, M., Fukasawa, K., Sato, H., Nakamura, R., Ohara, O., & Kawashima, Y. (2022) · Journal of Proteome Research · doi:10.1021/acs.jproteome.2c00121 · Cited by 37 · see citing works

Parallelization with Dual-Trap Single-Column Configuration Maximizes Throughput of Proteomic Analysis

Kreimer, S. D., Haghani, A., Binek, A., Hauspurg, A. K., Seyedmohammad, S., Rivas, A., Momenzadeh, A., Meyer, J. G., Raedschelders, K., & Eyk, J. E. V. (2022) · Analytical Chemistry · doi:10.1021/acs.analchem.2c02609 · Cited by 35 · see citing works

Development of a Gill Assay Library for Ecological Proteomics of Threespine Sticklebacks (Gasterosteus aculeatus)

Li, J., Levitan, B. B., Gómez‐Jiménez, S., & Kültz, D. (2018) · Molecular & Cellular Proteomics · doi:10.1074/mcp.ra118.000973 · Cited by 34 · see citing works

Proteome and Secretome Dynamics of Human Retinal Pigment Epithelium in Response to Reactive Oxygen Species

Meyer, J. G., Garcia, T. Y., Schilling, B., Gibson, B. W., & Lamba, D. A. (2019) · Scientific Reports · doi:10.1038/s41598-019-51777-7 · Cited by 33 · see citing works

Insights into the role of androgen receptor in human testicular peritubular cells

Mayer, C. A., Adam, M., Walenta, L., Schmid, N., Heikelä, H., Schubert, K., Flenkenthaler, F., Dietrich, K.-G., Gruschka, S., Arnold, G. J., et al. (2018) · Andrology · doi:10.1111/andr.12509 · Cited by 33 · see citing works

Quantitative Analysis of Target Peptides Related to Resistance Against Ascochyta Blight (Peyronellaea pinodes) in Pea

Castillejo, M. Á., Fondevilla, S., Fuentes-Almagro, C. A., & Rubiales, D. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.9b00365 · Cited by 32 · see citing works

THE PRESENT AND FUTURE OF THE MASS SPECTROMETRY-BASED INVESTIGATION OF THE EXOSOME LANDSCAPE.

Xu, L., Gimple, R., Lau, W., Lau, B., Fei, F., Shen, Q., Liao, X., Li, Y., Wang, W., He, Y., et al. (2020) · Mass spectrometry reviews (Print) · doi:10.1002/mas.21635 · Cited by 29 · see citing works

Mass spectrometry-based phosphoproteomics in clinical applications

Wu, X., Liu, Y., Iliuk, A. B., & Tao, W. A. (2023) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2023.117066 · Cited by 31 · see citing works

SWATH-MS analysis of cerebrospinal fluid to generate a robust battery of biomarkers for Alzheimer’s disease

Park, S. A., Jung, J. M., Park, J. S., Lee, J. H., Park, B., Kim, H. J., Park, J., Chae, W. S., Jeong, J. H., Choi, S. H., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-64461-y · Cited by 30 · see citing works

Quantification of biomarkers for beef meat qualities using a combination of Parallel Reaction Monitoring- and antibody-based proteomics

Bonnet, M., Soulat, J., Bons, J., Leger, S., de Koning, L., Carapito, C., & Picard, B. B. (2020) · Food Chemistry · doi:10.1016/j.foodchem.2020.126376 · Cited by 29 · see citing works

DIAproteomics: A Multifunctional Data Analysis Pipeline for Data-Independent Acquisition Proteomics and Peptidomics

Bichmann, L., Gupta, S., Rosenberger, G., Kuchenbecker, L., Sachsenberg, T. T., Ewels, P., Alka, O., Pfeuffer, J., Kohlbacher, O., & Röst, H. L. (2021) · Journal of Proteome Research · doi:10.1021/acs.jproteome.1c00123 · Cited by 29 · see citing works

Proteomic Approaches to Study Cysteine Oxidation: Applications in Neurodegenerative Diseases

Pham, T. K., Buczek, W. A., Mead, R. J., Shaw, P. J., & Collins, M. O. (2021) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2021.678837 · Cited by 28 · see citing works

Mass spectrometry as a tool for biomarkers searching in gynecological oncology

Banach, P., Suchy, W., Dereziński, P., Matysiak, J., Kokot, Z. J., & Nowak‐Markwitz, E. (2017) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2017.05.146 · Cited by 28 · see citing works

Single-cell proteomics using mass spectrometry

Momenzadeh, A., & Meyer, J. G. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.100973 · Cited by 27 · see citing works

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Kobeissy, F. H., Goli, M., Yadikar, H., Shakkour, Z., Kurup, M., Haidar, M. A., Alroumi, S., Mondello, S., Wang, K., & Mechref, Y. S. (2023) · Frontiers in Neurology · doi:10.3389/fneur.2023.1288740 · Cited by 27 · see citing works

Surveying the Vampire Bat ( Desmodus rotundus ) Serum Proteome: A Resource for Identifying Immunological Proteins and Detecting Pathogens

Neely, B. A., Janech, M. G., Fenton, M. B., Simmons, N. B., Bland, A. M., & Becker, D. J. (2021) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00995 · Cited by 24 · see citing works

Detection of Circulating Serum Protein Biomarkers of Non-Muscle Invasive Bladder Cancer after Protein Corona-Silver Nanoparticles Analysis by SWATH-MS

Gómez, B. B., López-Cortés, R., Nebra, J. C., Vázquez‐Estévez, S., Pérez-Fentes, D., Chantada‐Vázquez, M. D. P., Bravo, S. B., & Núñez, C. (2021) · Nanomaterials · doi:10.3390/nano11092384 · Cited by 24 · see citing works

Metaproteomics Analysis of SARS-CoV-2-Infected Patient Samples Reveals Presence of Potential Coinfecting Microorganisms

Thuy-Boun, P. S., Mehta, S., Gruening, B., McGowan, T. F., Nguyen, A., Rajczewski, A. T., Johnson, J. E., Griffin, T. J., Wolan, D. W., & Jagtap, P. D. (2021) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00822 · Cited by 23 · see citing works

The use of data independent acquisition based proteomic analysis and machine learning to reveal potential biomarkers for autism spectrum disorder

Zhang, H., Tang, X., Feng, C., Gao, Y. L., Hong, Q., Zhang, J., Zhang, X., Zheng, Q., Jing, L., Liu, X., et al. (2023) · Journal of Proteomics · doi:10.1016/j.jprot.2023.104872 · Cited by 23 · see citing works

Comprehensive spectral libraries for various rabbit eye tissue proteomes

Qin, G., Zhang, P., Sun, M., Fu, W., & Cai, C. (2022) · Scientific Data · doi:10.1038/s41597-022-01241-5 · Cited by 22 · see citing works

Global View of Candidate Therapeutic Target Genes in Hormone-Responsive Breast Cancer

Salvati, A., Gigantino, V., Nassa, G., Cappa, V. M., Ventola, G. M., Cracas, D. G. C., Mastrocinque, R., Rizzo, F. M., Tarallo, R., Weisz, A., et al. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21114068 · Cited by 21 · see citing works

Applications of multiple reaction monitoring targeted proteomics assays in human plasma

Kontostathi, G., Makridakis, M., Zoidakis, J., & Vlahou, A. (2019) · Expert Review of Molecular Diagnostics · doi:10.1080/14737159.2019.1615448 · Cited by 21 · see citing works

Bottom-up proteomic analysis of human adult cardiac tissue and isolated cardiomyocytes

Wojtkiewicz, M. S., Luecke, L. B., Castro, C., Burkovetskaya, M. E., Mesidor, R., & Gundry, R. L. (2021) · Journal of Molecular and Cellular Cardiology · doi:10.1016/j.yjmcc.2021.08.008 · Cited by 20 · see citing works

Neuronal glycogen breakdown mitigates tauopathy via pentose-phosphate-pathway-mediated oxidative stress reduction

Bar, S., Wilson, K. A., Hilsabeck, T. A. U., Alderfer, S. A., Dammer, E. B., Burton, J. B., Shah, S., Holtz, A. N., Carrera, E. M., Beck, J. N., et al. (2025) · Nature Metabolism · doi:10.1038/s42255-025-01314-w · Cited by 19 · see citing works

Degradomics in Biomarker Discovery

Grozdanić, M., Vidmar, R., Vizovišek, M., & Fonovič, M. (2019) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201800138 · Cited by 19 · see citing works

Prostate Cancer Biomarker Development: National Cancer Institute's Early Detection Research Network Prostate Cancer Collaborative Group Review

Liss, M. A., Leach, R. J., Sanda, M. G., & Semmes, O. J. (2020) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-20-1104 · Cited by 18 · see citing works

The Implementation of Mass Spectrometry-Based Proteomics Workflows in Clinical Routines of Acute Myeloid Leukemia: Applicability and Perspectives

Hernandez-Valladares, M., Bruserud, Ø., & Selheim, F. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21186830 · Cited by 18 · see citing works

CsoDIAq Software for Direct Infusion Shotgun Proteome Analysis

Cranney, C., & Meyer, J. G. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.1c02021 · Cited by 18 · see citing works

Proteomic Profiling Towards a Better Understanding of Genetic Based Muscular Diseases: The Current Picture and a Look to the Future

Pauper, M., Hentschel, A., Tiburcy, M., Beltrán, S., Ruck, T., Schara, U., & Roos, A. (2025) · Biomolecules · doi:10.3390/biom15010130 · Cited by 17 · see citing works

Data Independent Acquisition Mass Spectrometry Can Identify Circulating Proteins That Predict Future Weight Loss with a Diet and Exercise Programme

Malipatil, N. S., Fachim, H., Siddals, K. W., Geary, B., Wark, G., Porter, N., Anderson, S. G., Donn, R. P., Harvie, M., Whetton, A. D., et al. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm8020141 · Cited by 17 · see citing works

LGALS3BP: A Potential Plasma Biomarker Associated with Diagnosis and Prognosis in Patients with Sepsis

Luo, M., Zhang, Q., Hu, Y., Sun, C., Sheng, Y., & Deng, C. (2021) · Infection and Drug Resistance · doi:10.2147/idr.s316402 · Cited by 17 · see citing works

Quantitative proteomics analysis of human vitreous in rhegmatogenous retinal detachment associated with choroidal detachment by data-independent acquisition mass spectrometry

Luo, S., Xu, H., Yang, L., Gong, X., Shen, J., Chen, X., & Wu, Z. (2022) · Molecular and Cellular Biochemistry · doi:10.1007/s11010-022-04409-0 · Cited by 17 · see citing works

Targeted proteomics for cancer biomarker verification and validation

Ogata, S., Masuda, T., Ito, S., & Ohtsuki, S. (2022) · Cancer Biomarkers · doi:10.3233/cbm-210218 · Cited by 17 · see citing works

Data‐independent acquisition and quantification of extracellular matrix from human lung in chronic inflammation‐associated carcinomas

Bons, J., Pan, D., Shah, S., Bai, R., Chen‐Tanyolac, C., Wang, X., Elliott, D. R. F., Urisman, A., O’Broin, A., Basisty, N., et al. (2022) · PROTEOMICS · doi:10.1002/pmic.202200021 · Cited by 17 · see citing works

Protein Abundance of Drug Metabolizing Enzymes in Human Hepatitis C Livers

Droździk, M., Łapczuk-Romańska, J., Wenzel, C., Skalski, Ł., Szeląg-Pieniek, S., Post, M., Parus, A., Wawrzynowicz‐Syczewska, M., Kurzawski, M., & Oswald, S. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24054543 · Cited by 17 · see citing works

Proteomics and frailty: a clinical overview

Danese, E., Montagnana, M., & Lippi, G. (2018) · Expert Review of Proteomics · doi:10.1080/14789450.2018.1505511 · Cited by 17 · see citing works

SWATH-MS Protocols in Human Diseases

Chantada‐Vázquez, M. D. P., García-Vence, M., Serna, A., Núñez, C., & Bravo, S. B. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1178-4_7 · Cited by 17 · see citing works

Proteomics Data Analysis for the Identification of Proteins and Derived Proteotypic Peptides of Potential Use as Putative Drought Tolerance Markers for Quercus ilex

San-Eufrasio, B., Bigattón, E. D., Guerrero-Sánchez, V. M., Chaturvedi, P., Jorrín-Novo, J. V., Rey, M.-D., & Castillejo, M. Á. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22063191 · Cited by 17 · see citing works

Proteomic Analysis in Morquio A Cells Treated with Immobilized Enzymatic Replacement Therapy on Nanostructured Lipid Systems

Álvarez, J. V., Bravo, S. B., García-Vence, M., de Castro, M. J., Álvarez, A. L., Colón, C., Tomatsu, S., Otero-Espinar, F. J., & Couce, M. L. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20184610 · Cited by 15 · see citing works

Urine Proteome Changes in a TNBS‐Induced Colitis Rat Model

Qin, W., Li, L., Wang, T., Huang, H., & Gao, Y. (2019) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201800100 · Cited by 15 · see citing works

A primary human T-cell spectral library to facilitate large scale quantitative T-cell proteomics

Weerakoon, H. T. W., Potriquet, J., Shah, A. K., Reed, S., Arachchige, B. J., Kapil, C., Midha, M. K., Moritz, R. L., Lepletier, A., Mulvenna, J. P., et al. (2020) · Scientific Data · doi:10.1038/s41597-020-00744-3 · Cited by 14 · see citing works

An omics review and perspective of researches on intrahepatic cholestasis of pregnancy

Wang, M., Chen, L., Li, J., You, Y., Qian, Z., Liu, J., Jiang, Y., Zhou, T., Gu, Y., & Zhang, Y. (2024) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1267195 · Cited by 14 · see citing works

Early-Stage Staphylococcus aureus Bloodstream Infection Causes Changes in the Concentrations of Lipoproteins and Acute-Phase Proteins and Is Associated with Low Antibody Titers against Bacterial Virulence Factors

Michalik, S., Sundaramoorthy, N., Murr, A., Depke, M., Völker, U., Bröker, B. M., Aamot, H. V., & Schmidt, F. (2020) · mSystems · doi:10.1128/msystems.00632-19 · Cited by 14 · see citing works

Multiple reaction monitoring assays for large-scale quantitation of proteins from 20 mouse organs and tissues

Michaud, S. A., Pětrošová, H., Sinclair, N. J. T., Kinnear, A. L., Jackson, A., McGuire, J. C., Hardie, D. B., Bhowmick, P., Ganguly, M., Flenniken, A. M., et al. (2024) · Communications Biology · doi:10.1038/s42003-023-05687-0 · Cited by 13 · see citing works

Comparative evaluation of peptidome and microbiota in different types of saliva samples

Zhu, C., Yuan, C., Wei, F., Sun, X., & Zheng, S.-G. (2020) · Annals of Translational Medicine · doi:10.21037/atm-20-393 · Cited by 13 · see citing works

Selenium-isotopic signature toward mass spectrometric identification and enzyme activity assay

Hu, J., Liu, F., Feng, N., & Ju, H. (2019) · Analytica Chimica Acta · doi:10.1016/j.aca.2019.03.045 · Cited by 13 · see citing works

Targeted Workflow Investigating Variations in the Tear Proteome by Liquid Chromatography Tandem Mass Spectrometry

Lépine, M., Zambito, O., & Sleno, L. (2023) · ACS Omega · doi:10.1021/acsomega.3c03186 · Cited by 12 · see citing works

Bone Proteomics Method Optimization for Forensic Investigations

Gent, L., Chiappetta, M. E., Hesketh, S. J., Palmowski, P., Porter, A., Bonicelli, A., Schwalbe, E. C., & Procopio, N. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c00151 · Cited by 12 · see citing works

Using SWATH ‐ MS to identify new molecular biomarkers in gingival crevicular fluid for detecting periodontitis and its response to treatment

Blanco‐Pintos, T., Regueira‐Iglesias, A., Relvas, M., Alonso‐Sampedro, M., Chantada‐Vázquez, M. D. P., Balsa‐Castro, C., & Tomás, I. (2024) · Journal Of Clinical Periodontology · doi:10.1111/jcpe.14037 · Cited by 12 · see citing works

Mass spectrometry based protein biomarkers and drug target discovery and clinical diagnosis in Age-Related progressing neurodegenerative diseases

Agrawal, I., Tripathi, P., & Biswas, S. (2022) · Drug Metabolism Reviews · doi:10.1080/03602532.2022.2029475 · Cited by 12 · see citing works

Proteomics and bioinformatics analyses based on two-dimensional electrophoresis and LC-MS/MS for the primary characterization of protein changes in chicken breast meat from divergent farming systems: Organic versus antibiotic-free

Alessandroni, L., Sagratini, G., & Gagaoua, M. (2024) · Food Chemistry Molecular Sciences · doi:10.1016/j.fochms.2024.100194 · Cited by 12 · see citing works

In Vivo Large-Scale Mapping of Protein Turnover in Human Cerebrospinal Fluid

Lehmann, S., Hirtz, C., Vialaret, J., Ory, M., Gras-Combe, G., Corre, M. L., Badiou, S., Cristol, J., Hanon, O., Cornillot, E., et al. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b03328 · Cited by 11 · see citing works

Exploring novel protein-based biomarkers for advancing breast cancer diagnosis: A review

Vellan, C. J., Islam, T., Silva, S. D., Taib, N. A. M., Prasanna, G., & Jayapalan, J. J. (2024) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2024.110776 · Cited by 11 · see citing works

Integrated Chemometrics and Data-Independent Acquisition Proteomics for the Discovery of Meat Authenticity Biomarkers: A Study on Early Post-Mortem Pectoralis major Muscle Proteomes of Ross 308 and Ranger Classic Chicken Produced by Organic versus Antibiotic-Free Farming Systems

Alessandroni, L., Sagratini, G., & Gagaoua, M. (2024) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.4c03651 · Cited by 11 · see citing works

Integrated mass spectrometry-based multi-omics for elucidating mechanisms of bacterial virulence

Man, L., Klare, W. P., Dale, A. L., Cain, J. A., & Cordwell, S. J. (2021) · Biochemical Society Transactions · doi:10.1042/bst20191088 · Cited by 11 · see citing works

Data-independent acquisition-based SWATH-MS proteomics profiling to decipher the impact of farming system and chicken strain and discovery of biomarkers of authenticity in organic versus antibiotic-free chicken meat

Alessandroni, L., Sagratini, G., Bravo, S. B., & Gagaoua, M. (2024) · Current Research in Food Science · doi:10.1016/j.crfs.2024.100757 · Cited by 11 · see citing works

Deciphering tissue‐based proteome signatures revealed novel subtyping and prognostic markers for thymic epithelial tumors

Ku, X., Sun, Q., Zhu, L., Gu, Z., Han, Y., Xu, N., Meng, C., Yang, X., Yan, W., & Fang, W. (2020) · Molecular Oncology · doi:10.1002/1878-0261.12642 · Cited by 12 · see citing works

Platform independent protein-based cell-of-origin subtyping of diffuse large B-cell lymphoma in formalin-fixed paraffin-embedded tissue

Reinders, J., Altenbuchinger, M., Limm, K., Schwarzfischer, P., Scheidt, T., Strasser, L., Richter, J., Szczepanowski, M., Huber, C. G., Klapper, W., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-64212-z · Cited by 10 · see citing works

Comprehensive N-Glycan Mapping using Parallel Reaction Monitoring LC–MS/MS

Shipman, J. J., Sommers, C. D., Keire, D. A., Chen, K., & Zhu, H. (2022) · Pharmaceutical Research · doi:10.1007/s11095-022-03453-1 · Cited by 10 · see citing works

Proteomics‐based mass spectrometry profiling of SARS‐CoV‐2 infection from human nasopharyngeal samples

Chatterjee, S., & Zaia, J. (2022) · Mass spectrometry reviews (Print) · doi:10.1002/mas.21813 · Cited by 7 · see citing works

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Xie, X., Shah, S., Holtz, A. N., Rose, J., Basisty, N., & Schilling, B. (2020) · Journal of Visualized Experiments · doi:10.3791/60780 · Cited by 9 · see citing works

Effect of dynamic exclusion and the use of FAIMS, DIA and MALDI-mass spectrometry imaging with ion mobility on amyloid protein identification

Aguilan, J. T., Lim, J., Racine‐Brzostek, S., Fischer, J. L., Silvescu, C., Cornett, S., Nieves, E., Mendu, D. R., Aliste, C.-M., Semple, S., et al. (2024) · Clinical Proteomics · doi:10.1186/s12014-024-09500-w · Cited by 8 · see citing works

Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection

Boada, P., Fatou, B., Belperron, A. A., Sigdel, T. K., Smolen, K. K., Wurie, Z., Levy, O., Ronca, S. E., Murray, K. O., Liberto, J. M., et al. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.1012824 · Cited by 8 · see citing works

Comprehensive Overview of Bottom-up Proteomics using Mass SpectrometryPreprint

Jiang, Y., Rex, D. A. B., Schuster, D., Neely, B. A., Rosano, G. L., Volkmar, N., Momenzadeh, A., Peters-Clarke, T. M., Egbert, S., Kreimer, S. D., et al. (2023) · PubMed · doi:10.48550/arxiv.2311.07791 · Cited by 8 · see citing works

Quantitative Proteomic Study Unmasks Fibrinogen Pathway in Polycystic Liver Disease

Cordido, A., Vizoso-González, M., Núñez-González, L., Molares-Vila, A., Chantada‐Vázquez, M. D. P., Bravo, S. B., & García-González, M. Á. (2022) · Biomedicines · doi:10.3390/biomedicines10020290 · Cited by 7 · see citing works

Digging Deeper Into Cardiovascular Plasma Proteomics: Opportunities and Limitations of Current Platforms

Chhay, P., Tang, O., Ai, L., Cordwell, S. J., Gray, M. P., Yang, J. Y. H., Eyk, J. E. V., Psaltis, P. J., & Figtree, G. A. (2025) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.125.005198 · Cited by 6 · see citing works

Oncoproteomics: insight into current proteomic technologies in cancer biomarker discovery and treatment

Dutta, S., Ghosh, S., Mishra, A. B., & Ghosh, R. (2022) · Journal of Proteins and Proteomics · doi:10.1007/s42485-022-00100-6 · Cited by 6 · see citing works

Mass Spectrometry-Based Proteomics for Classification and Treatment Optimisation of Triple Negative Breast Cancer

metwali, E., & Pennington, S. R. (2024) · Journal of Personalized Medicine · doi:10.3390/jpm14090944 · Cited by 6 · see citing works

A novel in-vitro expression assay by LC/MS/MS enables multi-antigen mRNA vaccine characterization

Wang, H. L., Kajbaf, K., Gau, B. C., Dawdy, A., Edwards, R., Bare, B., Raymundo, G., Iturrizaga, J., Ernsky, C., Walker, M. S., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-94616-8 · Cited by 6 · see citing works

Integrating site-specific peptide reporters and targeted mass spectrometry enables rapid substrate-specific kinase assay at the nanogram cell level

Reyes, A. J. F., Kitata, R. B., Rosa, M. A. C. D., Wang, Y.-T., Lin, P.-Y., Yang, P., Friedler, A., Yitzchaik, S., & Chen, Y. (2021) · Analytica Chimica Acta · doi:10.1016/j.aca.2021.338341 · Cited by 6 · see citing works

Advanced mass spectrometry-based methods for protein molecular-structural biologists

Bons, J., Rose, J., O’Broin, A., & Schilling, B. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90264-9.00020-9 · Cited by 5 · see citing works

HNRNPA2B1 as a potential therapeutic target for thymic epithelial tumor recurrence: An integrative network analysis

Zhou, Z., Lu, Y., Gu, Z., Sun, Q., Fang, W., Yan, W., Ku, X., Liang, Z. T., & Hu, G. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.106665 · Cited by 6 · see citing works

SWATH proteomics analysis of placental tissue with intrahepatic cholestasis of pregnancy

Jiang, Y., Yin, X., Xu, Q. J., Tang, X., Zhang, H., Cao, X., Jing, L., Wang, Y., Yang, F., Khan, N. U., et al. (2023) · Placenta · doi:10.1016/j.placenta.2023.04.009 · Cited by 6 · see citing works

Perspectives and opinions from scientific leaders on the evolution of data-independent acquisition for quantitative proteomics and novel biological applications

Hunter, C. L., Bons, J., & Schilling, B. (2023) · Australian Journal of Chemistry · doi:10.1071/ch23039 · Cited by 6 · see citing works

DIAproteomics: A multi-functional data analysis pipeline for data-independent-acquisition proteomics and peptidomicsPreprint

Bichmann, L., Gupta, S., Rosenberger, G., Kuchenbecker, L., Sachsenberg, T. T., Alka, O., Pfeuffer, J., Kohlbacher, O., & Röst, H. L. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.12.08.415844 · Cited by 6 · see citing works

Advances in targeted proteomics and applications to biomedical research

Shi, T., Song, E., Nie, S., Rodland, K., Liu, T., Qian, W., & Smith, R. D. (2016) · PROTEOMICS · doi:10.1002/pmic.201500449 · Cited by 259 · see citing works

Exploring the Potential of Data-Independent Acquisition Proteomics Using Untargeted All-Ion Quantitation: Application to Tumor Subtype Diagnosis

Yan, Z., & Yan, R. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.7b03920 · Cited by 3 · see citing works

A review on mass spectrometry-based quantitative proteomics: Targeted and data independent acquisition

Vidová, V., & Spáčil, Z. (2017) · Analytica Chimica Acta · doi:10.1016/j.aca.2017.01.059 · Cited by 353 · see citing works

Using data‐independent, high‐resolution mass spectrometry in protein biomarker research: Perspectives and clinical applications

Sajic, T., Liu, Y., & Aebersold, R. H. (2014) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201400117 · Cited by 209 · see citing works

Evaluation of SRM-, PRM- and DIA-based Targeted Quantification

Omics, P., Song, E., Shi, T., Wang, H., Shukla Anil, K., Fillmore, T. L., Gao, Y., Nie, S., Moore, R. J., Gaffrey, M. J., et al. (2017) · Figshare · doi:10.6084/m9.figshare.5110918