Mapping Biological Networks from Quantitative Data-Independent Acquisition Mass Spectrometry: Data to Knowledge Pipelines
Open accessAbstract
Data-independent acquisition mass spectrometry (DIA-MS) strategies and applications provide unique advantages for qualitative and quantitative proteome probing of a biological sample allowing constant sensitivity and reproducibility across large sample sets. These advantages in LC-MS/MS are being realized in fundamental research laboratories and for clinical research applications. However, the ability to translate high-throughput raw LC-MS/MS proteomic data into biological knowledge is a complex and difficult task requiring the use of many algorithms and tools for which there is no widely accepted standard and best practices are slowly being implemented. Today a single tool or approach inherently fails to capture the full interpretation that proteomics uniquely supplies, including the dynamics of quickly reversible chemically modified states of proteins, irreversible amino acid modifications, signaling truncation events, and, finally, determining the presence of protein from allele-specific transcripts. This chapter highlights key steps and publicly available algorithms required to translate DIA-MS data into knowledge.
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DIA results in identification of nearly all detectable peptides within a selected mass range, allowing comprehensive and accurate quantification of identified proteins with minimal missing values.
“Therefore, DIA results in the identification of nearly all detectable peptides within a selected mass range, allowing for comprehensive and accurate quantification of identified proteins in the sample with minimal missing values [81, 82].”
From Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau (2021) · cites this paper as [82]
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- Authors
- Crowgey, E. L., Matlock, A., Venkatraman, V., Fert-Bober, J., & Van Eyk, J. E.
- Affiliations
- Alfred I. duPont Hospital for Children (US)
- Cedars-Sinai Medical Center (US)
- Corresponding author
- Crowgey, Erin L.
- Venue
- Methods in Molecular Biology
- Publisher
- Springer New York
- Published
- 2017
- Volume
- 1558
- Pages
- 395-413
- ISSN
- 1064-3745 (ISSN-L)
- 1940-6029
- PMC
- PMC6844627
- OpenAlex
- W2585647902
- Cited by
- 9
- References
- 60
- Citations by year
- 2025: 1 · 2023: 2 · 2022: 1 · 2021: 1 · 2020: 1 · 2019: 1 · 2018: 1 · 2017: 1
- FWCI
- 4.48
- Type
- book chapter
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Methods in molecular biology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Heart, Lung, and Blood Institute (R01HL101235, R01HL132075)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Keywords
- data-independent acquisition mass spectrometry, quantitative proteomics, protein chemical modification, amino acid modification, protein truncation
- MeSH terms
- Peptides, Software, Mass Spectrometry, User-Computer Interface, Computational Biology, Gene Regulatory Networks, Data Mining, Protein Interaction Maps, Web Browser
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