Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,029

The DOI matches its Crossref record.

Statistical Analysis of Membrane Proteome Expression Changes in Saccharomyces cerevisiae

Zybailov, Boris, Mosley, Amber L., Sardiu, Mihaela E., Coleman, Michael K., Florens, Laurence, Washburn, Michael P.·2006·Journal of Proteome Research

Abstract

We have devised an approach for analyzing shotgun proteomics datasets based on the normalized spectral abundance factor that can be used for quantitative proteomics analysis. Three biological replicates of samples enriched for plasma membranes were isolated from S. cerevisiae grown in 14N-rich media and 15N-minimal media and analyzed via quantitative multidimensional protein identification technology. The natural log transformation of NSAF values from S. cerevisiae cells grown in 14N YPD media and 15N-minimal media had a normal distribution. The t-test analysis demonstrated 221 of 1316 proteins were significantly overexpressed in one or the other growth conditions with a p value <0.05. Notably, amino acid transporters were among the 14 membrane proteins that were significantly upregulated in cells grown in minimal media, and we functionally validated these increases in protein expression with radioisotope uptake assays for selected proteins.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/pr060161n

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 1,029

Metadata

Authors
Zybailov, B., Mosley, A. L., Sardiu, M. E., Coleman, M. K., Florens, L., & Washburn, M. P.
Venue
Journal of Proteome Research
Published
2006-07-29
Volume
5
Issue
9
Pages
2339-2347
ISSN
  • 1535-3893 (ISSN-L)
  • 1535-3907
OpenAlex
W2053894359
Cited by
1,029
References
0
FWCI
13.46
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Statistical Analysis of Membrane Proteome Expression Changes in Saccharomyces cerevisiae. https://app.cochat.ai/papers/10.1021/pr060161n
The paper
Zybailov, B., Mosley, A. L., Sardiu, M. E., Coleman, M. K., Florens, L., & Washburn, M. P. (2006). Statistical Analysis of Membrane Proteome Expression Changes in Saccharomyces cerevisiae. Journal of Proteome Research. https://doi.org/10.1021/pr060161n

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.