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Protein identification from two-dimensional gel electrophoresis analysis of Klebsiella pneumoniae by combined use of mass spectrometry data and raw genome sequences

Overview of attention for article published in Proteome Science, December 2003
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  • Among the highest-scoring outputs from this source (#45 of 208)

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6 Wikipedia pages

Citations

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31 Dimensions

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76 Mendeley
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1 CiteULike
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Title
Protein identification from two-dimensional gel electrophoresis analysis of Klebsiella pneumoniae by combined use of mass spectrometry data and raw genome sequences
Published in
Proteome Science, December 2003
DOI 10.1186/1477-5956-1-6
Pubmed ID
Authors

Wei Wang, Jibin Sun, Manfred Nimtz, Wolf-Dieter Deckwer, An-Ping Zeng

Abstract

Separation of proteins by two-dimensional gel electrophoresis (2-DE) coupled with identification of proteins through peptide mass fingerprinting (PMF) by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is the widely used technique for proteomic analysis. This approach relies, however, on the presence of the proteins studied in public-accessible protein databases or the availability of annotated genome sequences of an organism. In this work, we investigated the reliability of using raw genome sequences for identifying proteins by PMF without the need of additional information such as amino acid sequences. The method is demonstrated for proteomic analysis of Klebsiella pneumoniae grown anaerobically on glycerol. For 197 spots excised from 2-DE gels and submitted for mass spectrometric analysis 164 spots were clearly identified as 122 individual proteins. 95% of the 164 spots can be successfully identified merely by using peptide mass fingerprints and a strain-specific protein database (ProtKpn) constructed from the raw genome sequences of K. pneumoniae. Cross-species protein searching in the public databases mainly resulted in the identification of 57% of the 66 high expressed protein spots in comparison to 97% by using the ProtKpn database. 10 dha regulon related proteins that are essential for the initial enzymatic steps of anaerobic glycerol metabolism were successfully identified using the ProtKpn database, whereas none of them could be identified by cross-species searching. In conclusion, the use of strain-specific protein database constructed from raw genome sequences makes it possible to reliably identify most of the proteins from 2-DE analysis simply through peptide mass fingerprinting.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 1%
India 1 1%
China 1 1%
France 1 1%
Unknown 72 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 28%
Researcher 13 17%
Student > Master 10 13%
Student > Bachelor 6 8%
Other 5 7%
Other 10 13%
Unknown 11 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 40 53%
Biochemistry, Genetics and Molecular Biology 7 9%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Immunology and Microbiology 3 4%
Engineering 3 4%
Other 7 9%
Unknown 12 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 October 2020.
All research outputs
#8,534,976
of 25,374,647 outputs
Outputs from Proteome Science
#45
of 208 outputs
Outputs of similar age
#36,132
of 142,789 outputs
Outputs of similar age from Proteome Science
#1
of 2 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 208 research outputs from this source. They receive a mean Attention Score of 2.8. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 142,789 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them