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Unipept 4.0 : functional analysis of metaproteome data

(2019) JOURNAL OF PROTEOME RESEARCH. 18(2). p.606-615
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Abstract
Unipept (https://unipept.ugent.be) is a web application for metaproteome data analysis, with an initial focus on tryptic-peptide-based biodiversity analysis of MS/MS samples. Because the true potential of metaproteomics lies in gaining insight into the expressed functions of complex environmental samples, the 4.0 release of Unipept introduces complementary functional analysis based on GO terms and EC numbers. Integration of this new functional analysis with the existing biodiversity analysis is an important asset of the extended pipeline. As a proof of concept, a human faecal metaproteome data set from 15 healthy subjects was reanalyzed with Unipept 4.0, yielding fast, detailed, and straightforward characterization of taxon-specific catalytic functions that is shown to be consistent with previous results from a BLAST-based functional analysis of the same data.
Keywords
Unipept, metaproteomics, functional analysis, biodiversity analysis, GO terms, EC numbers, data analysis, data visualization, GENE ONTOLOGY, MICROBIOTA, TOOL

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

MLA
Gurdeep Singh, Robbert et al. “Unipept 4.0 : Functional Analysis of Metaproteome Data.” JOURNAL OF PROTEOME RESEARCH 18.2 (2019): 606–615. Print.
APA
Gurdeep Singh, R., Tanca, A., Palomba, A., Van der Jeugt, F., Verschaffelt, P., Uzzau, S., Martens, L., et al. (2019). Unipept 4.0 : functional analysis of metaproteome data. JOURNAL OF PROTEOME RESEARCH, 18(2), 606–615.
Chicago author-date
Gurdeep Singh, Robbert, Alessandro Tanca, Antonio Palomba, Felix Van der Jeugt, Pieter Verschaffelt, Sergio Uzzau, Lennart Martens, Peter Dawyndt, and Bart Mesuere. 2019. “Unipept 4.0 : Functional Analysis of Metaproteome Data.” Journal of Proteome Research 18 (2): 606–615.
Chicago author-date (all authors)
Gurdeep Singh, Robbert, Alessandro Tanca, Antonio Palomba, Felix Van der Jeugt, Pieter Verschaffelt, Sergio Uzzau, Lennart Martens, Peter Dawyndt, and Bart Mesuere. 2019. “Unipept 4.0 : Functional Analysis of Metaproteome Data.” Journal of Proteome Research 18 (2): 606–615.
Vancouver
1.
Gurdeep Singh R, Tanca A, Palomba A, Van der Jeugt F, Verschaffelt P, Uzzau S, et al. Unipept 4.0 : functional analysis of metaproteome data. JOURNAL OF PROTEOME RESEARCH. 2019;18(2):606–15.
IEEE
[1]
R. Gurdeep Singh et al., “Unipept 4.0 : functional analysis of metaproteome data,” JOURNAL OF PROTEOME RESEARCH, vol. 18, no. 2, pp. 606–615, 2019.
@article{8583174,
  abstract     = {Unipept (https://unipept.ugent.be) is a web application for metaproteome data analysis, with an initial focus on tryptic-peptide-based biodiversity analysis of MS/MS samples. Because the true potential of metaproteomics lies in gaining insight into the expressed functions of complex environmental samples, the 4.0 release of Unipept introduces complementary functional analysis based on GO terms and EC numbers. Integration of this new functional analysis with the existing biodiversity analysis is an important asset of the extended pipeline. As a proof of concept, a human faecal metaproteome data set from 15 healthy subjects was reanalyzed with Unipept 4.0, yielding fast, detailed, and straightforward characterization of taxon-specific catalytic functions that is shown to be consistent with previous results from a BLAST-based functional analysis of the same data.},
  author       = {Gurdeep Singh, Robbert and Tanca, Alessandro and Palomba, Antonio and Van der Jeugt, Felix and Verschaffelt, Pieter and Uzzau, Sergio and Martens, Lennart and Dawyndt, Peter and Mesuere, Bart},
  issn         = {1535-3893},
  journal      = {JOURNAL OF PROTEOME RESEARCH},
  keywords     = {Unipept,metaproteomics,functional analysis,biodiversity analysis,GO terms,EC numbers,data analysis,data visualization,GENE ONTOLOGY,MICROBIOTA,TOOL},
  language     = {eng},
  number       = {2},
  pages        = {606--615},
  title        = {Unipept 4.0 : functional analysis of metaproteome data},
  url          = {http://dx.doi.org/10.1021/acs.jproteome.8b00716},
  volume       = {18},
  year         = {2019},
}

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