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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Organic Mass Spectro...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Organic Mass Spectrometry
Article . 2008 . Peer-reviewed
License: Wiley Online Library User Agreement
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Using enrichment index for quality control of secretory protein sample and identification of secretory proteins

Authors: Yong, Chen; Bei, Gu; Shuzhen, Wu; Wei, Sun; Sucan, Ma; Yuqin, Liu; Youhe, Gao;

Using enrichment index for quality control of secretory protein sample and identification of secretory proteins

Abstract

AbstractAnalysis of secretory proteins is an important area in proteomic research. We propose that a good secretory protein sample should be enriched with known secretory proteins, and a secretory protein should be enriched in the secretory protein sample compared with its corresponding soluble cell lysate. Positive identifications of proteins were subjected to quantitation of spectral counts, which reflect relative protein abundance. Enrichment index of the sample (EIS) and the enrichment index for protein (EIP) were obtained by comparing proteins identified in the secretory protein sample and those in the soluble cell lysate sample. The quality of the secretory protein sample can be represented by EIS. EIP was used to identify the secretory proteins.The secretory proteins from mouse dendritic cell sarcoma (DCS) were analyzed by MS. The EISs of two samples were 75.4 and 84.65, respectively. 72 proteins were significantly enriched in secretory protein samples, of which 42 proteins were either annotated in Swiss‐Prot and/or predicted by signal peptides to be secretory. In the remaining 30 proteins, 12 and 15 proteins were positively predicted by SecretomeP and ProP, respectively, and 5 proteins were positive by both methods. Furthermore, 11 proteins were found to be present in exosome in other studies that involved mice dendritic cell lines. We suggest that this assessment method is helpful for systemic research of secretory proteins and biomarker discovery for diseases such as cancer. Copyright © 2008 John Wiley & Sons, Ltd.

Keywords

Proteomics, Statistics as Topic, Proteins, Protein Sorting Signals, Mice, Solubility, Tandem Mass Spectrometry, Cell Line, Tumor, Animals, False Positive Reactions, Databases, Protein, Software, Chromatography, Liquid

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Average
Average
Top 10%
Related to Research communities
Cancer Research
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