Advanced search
1 file | 949.17 KB

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
Author
Organization
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.
Keywords
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

Downloads

  • acs.jproteome.6b01066.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 949.17 KB

Citation

Please use this url to cite or link to this publication:

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.
@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},
}

Altmetric
View in Altmetric
Web of Science
Times cited: