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A golden age for working with public proteomics data

Lennart Martens UGent and Juan Antonio Vizcaíno (2017) TRENDS IN BIOCHEMICAL SCIENCES. 42(5). p.333-341
abstract
Data sharing in mass spectrometry (MS)-based proteomics is becoming a common scientific practice, as is now common in the case of other, more mature 'omics' disciplines like genomics and transcriptomics. We want to highlight that this situation, unprecedented in the field, opens a plethora of opportunities for data scientists. First, we explain in some detail some of the work already achieved, such as systematic reanalysis efforts. We also explain existing applications of public proteomics data, such as proteogenomics and the creation of spectral libraries and spectral archives. Finally, we discuss the main existing challenges and mention the first attempts to combine public proteomics data with other types of omics data sets.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (review)
publication status
published
subject
keyword
MASS-SPECTROMETRY, PROTEOGENOMIC CHARACTERIZATION, PROTEIN IDENTIFICATION, PEPTIDE IDENTIFICATION, PHOSPHOPROTEOMICS DATA, QUALITY ASSESSMENT, PRIDE INSPECTOR, DATA STANDARD, GENOME, PROTEOMEXCHANGE
journal title
TRENDS IN BIOCHEMICAL SCIENCES
Trends Biochem.Sci.
volume
42
issue
5
pages
333 - 341
Web of Science type
Review
Web of Science id
000399985800004
ISSN
0968-0004
DOI
10.1016/j.tibs.2017.01.001
language
English
UGent publication?
yes
classification
A1
copyright statement
Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
id
8524756
handle
http://hdl.handle.net/1854/LU-8524756
date created
2017-06-22 12:48:01
date last changed
2017-09-25 08:05:08
@article{8524756,
  abstract     = {Data sharing in mass spectrometry (MS)-based proteomics is becoming a common scientific practice, as is now common in the case of other, more mature 'omics' disciplines like genomics and transcriptomics. We want to highlight that this situation, unprecedented in the field, opens a plethora of opportunities for data scientists. First, we explain in some detail some of the work already achieved, such as systematic reanalysis efforts. We also explain existing applications of public proteomics data, such as proteogenomics and the creation of spectral libraries and spectral archives. Finally, we discuss the main existing challenges and mention the first attempts to combine public proteomics data with other types of omics data sets.},
  author       = {Martens, Lennart and Vizca{\'i}no, Juan Antonio},
  issn         = {0968-0004},
  journal      = {TRENDS IN BIOCHEMICAL SCIENCES},
  keyword      = {MASS-SPECTROMETRY,PROTEOGENOMIC CHARACTERIZATION,PROTEIN IDENTIFICATION,PEPTIDE IDENTIFICATION,PHOSPHOPROTEOMICS DATA,QUALITY ASSESSMENT,PRIDE INSPECTOR,DATA STANDARD,GENOME,PROTEOMEXCHANGE},
  language     = {eng},
  number       = {5},
  pages        = {333--341},
  title        = {A golden age for working with public proteomics data},
  url          = {http://dx.doi.org/10.1016/j.tibs.2017.01.001},
  volume       = {42},
  year         = {2017},
}

Chicago
Martens, Lennart, and Juan Antonio Vizcaíno. 2017. “A Golden Age for Working with Public Proteomics Data.” Trends in Biochemical Sciences 42 (5): 333–341.
APA
Martens, Lennart, & Vizcaíno, J. A. (2017). A golden age for working with public proteomics data. TRENDS IN BIOCHEMICAL SCIENCES, 42(5), 333–341.
Vancouver
1.
Martens L, Vizcaíno JA. A golden age for working with public proteomics data. TRENDS IN BIOCHEMICAL SCIENCES. 2017;42(5):333–41.
MLA
Martens, Lennart, and Juan Antonio Vizcaíno. “A Golden Age for Working with Public Proteomics Data.” TRENDS IN BIOCHEMICAL SCIENCES 42.5 (2017): 333–341. Print.