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Unbiased protein association study on the public human proteome reveals biological connections between co-occurring protein pairs

Surya Gupta UGent, Kenneth Verheggen UGent, Jan Tavernier UGent and Lennart Martens UGent (2017) JOURNAL OF PROTEOME RESEARCH. 16(6). p.2204-2212
abstract
Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal wayS to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
computational analysis, mass spectrometry, pathways, protein co-occurrence, protein complex, protein−protein interaction, proteomics, REACTOME PATHWAY KNOWLEDGEBASE, INTERACTION NETWORKS, DATA SETS, DATABASE, PRIDE, IDENTIFICATION, EXPRESSION, BIOMARKERS, SPECTRA, UPDATE
journal title
JOURNAL OF PROTEOME RESEARCH
J. Proteome Res.
volume
16
issue
6
pages
2204 - 2212
Web of Science type
Article
Web of Science id
000402850800008
ISSN
1535-3893
1535-3907
DOI
10.1021/acs.jproteome.6b01066
language
English
UGent publication?
yes
classification
A1
copyright statement
I have retained and own the full copyright for this publication
id
8520500
handle
http://hdl.handle.net/1854/LU-8520500
date created
2017-05-16 07:44:07
date last changed
2017-07-05 08:24:02
@article{8520500,
  abstract     = {Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal wayS to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis.},
  author       = {Gupta, Surya and Verheggen, Kenneth and Tavernier, Jan and Martens, Lennart},
  issn         = {1535-3893},
  journal      = {JOURNAL OF PROTEOME RESEARCH},
  keyword      = {computational analysis,mass spectrometry,pathways,protein co-occurrence,protein complex,protein\ensuremath{-}protein interaction,proteomics,REACTOME PATHWAY KNOWLEDGEBASE,INTERACTION NETWORKS,DATA SETS,DATABASE,PRIDE,IDENTIFICATION,EXPRESSION,BIOMARKERS,SPECTRA,UPDATE},
  language     = {eng},
  number       = {6},
  pages        = {2204--2212},
  title        = {Unbiased protein association study on the public human proteome reveals biological connections between co-occurring protein pairs},
  url          = {http://dx.doi.org/10.1021/acs.jproteome.6b01066},
  volume       = {16},
  year         = {2017},
}

Chicago
Gupta, Surya, Kenneth Verheggen, Jan Tavernier, and Lennart Martens. 2017. “Unbiased Protein Association Study on the Public Human Proteome Reveals Biological Connections Between Co-occurring Protein Pairs.” Journal of Proteome Research 16 (6): 2204–2212.
APA
Gupta, Surya, Verheggen, K., Tavernier, J., & Martens, L. (2017). Unbiased protein association study on the public human proteome reveals biological connections between co-occurring protein pairs. JOURNAL OF PROTEOME RESEARCH, 16(6), 2204–2212.
Vancouver
1.
Gupta S, Verheggen K, Tavernier J, Martens L. Unbiased protein association study on the public human proteome reveals biological connections between co-occurring protein pairs. JOURNAL OF PROTEOME RESEARCH. 2017;16(6):2204–12.
MLA
Gupta, Surya, Kenneth Verheggen, Jan Tavernier, et al. “Unbiased Protein Association Study on the Public Human Proteome Reveals Biological Connections Between Co-occurring Protein Pairs.” JOURNAL OF PROTEOME RESEARCH 16.6 (2017): 2204–2212. Print.