Mapping biological networks from quantitative data-independent acquisition mass spectrometry: Data to knowledge pipelines

Erin L. Crowgey, Andrea Matlock, Vidya Venkatraman, Justyna Fert-Bober, Jennifer E. van Eyk

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages395-413
Number of pages19
Volume1558
DOIs
StatePublished - 2017
Externally publishedYes

Publication series

NameMethods in Molecular Biology
Volume1558
ISSN (Print)10643745

Fingerprint

Proteomics
Mass Spectrometry
Proteome
Practice Guidelines
Research
Proteins
Alleles
Amino Acids

Keywords

  • Citrullination
  • Data-independent acquisition
  • Phosphorylation
  • Post-translational modifications
  • Protein networks
  • SWATH

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

Cite this

Crowgey, E. L., Matlock, A., Venkatraman, V., Fert-Bober, J., & van Eyk, J. E. (2017). Mapping biological networks from quantitative data-independent acquisition mass spectrometry: Data to knowledge pipelines. In Methods in Molecular Biology (Vol. 1558, pp. 395-413). (Methods in Molecular Biology; Vol. 1558). Humana Press Inc.. https://doi.org/10.1007/978-1-4939-6783-4_19

Mapping biological networks from quantitative data-independent acquisition mass spectrometry : Data to knowledge pipelines. / Crowgey, Erin L.; Matlock, Andrea; Venkatraman, Vidya; Fert-Bober, Justyna; van Eyk, Jennifer E.

Methods in Molecular Biology. Vol. 1558 Humana Press Inc., 2017. p. 395-413 (Methods in Molecular Biology; Vol. 1558).

Research output: Chapter in Book/Report/Conference proceedingChapter

Crowgey, EL, Matlock, A, Venkatraman, V, Fert-Bober, J & van Eyk, JE 2017, Mapping biological networks from quantitative data-independent acquisition mass spectrometry: Data to knowledge pipelines. in Methods in Molecular Biology. vol. 1558, Methods in Molecular Biology, vol. 1558, Humana Press Inc., pp. 395-413. https://doi.org/10.1007/978-1-4939-6783-4_19
Crowgey EL, Matlock A, Venkatraman V, Fert-Bober J, van Eyk JE. Mapping biological networks from quantitative data-independent acquisition mass spectrometry: Data to knowledge pipelines. In Methods in Molecular Biology. Vol. 1558. Humana Press Inc. 2017. p. 395-413. (Methods in Molecular Biology). https://doi.org/10.1007/978-1-4939-6783-4_19
Crowgey, Erin L. ; Matlock, Andrea ; Venkatraman, Vidya ; Fert-Bober, Justyna ; van Eyk, Jennifer E. / Mapping biological networks from quantitative data-independent acquisition mass spectrometry : Data to knowledge pipelines. Methods in Molecular Biology. Vol. 1558 Humana Press Inc., 2017. pp. 395-413 (Methods in Molecular Biology).
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