Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 174

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Analysis of endoplasmic reticulum trafficking signals by combinatorial screening in mammalian cells

Open access
Zerangue, Noa, Malan, Michael J., Fried, Sharon R., Dazin, Paul F., Jan, Yuh Nung, Jan, Lily Yeh, Schwappach, Blanche·2001·Proceedings of the National Academy of Sciences

Abstract

To improve the accuracy of predicting membrane protein sorting signals, we developed a general methodology for defining trafficking signal consensus sequences in the environment of the living cell. Our approach uses retroviral gene transfer to create combinatorial expression libraries of trafficking signal variants in mammalian cells, flow cytometry to sort cells based on trafficking phenotype, and quantitative trafficking assays to measure the efficacy of individual signals. Using this strategy to analyze arginine- and lysine-based endoplasmic reticulum localization signals, we demonstrate that small changes in the local sequence context dramatically alter signal strength, generating a broad spectrum of trafficking phenotypes. Finally, using sequences from our screen, we found that the potency of di-lysine, but not di-arginine, mediated endoplasmic reticulum localization was correlated with the strength of interaction with α-COP.

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 · 10.1073/pnas.051630198

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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

Cites

Cited by

See all 174

Metadata

Authors
Zerangue, N., Malan, M. J., Fried, S. R., Dazin, P. F., Jan, Y. N., Jan, L. Y., & Schwappach, B.
Venue
Proceedings of the National Academy of Sciences
Published
2001-02-27
Volume
98
Issue
5
Pages
2431-2436
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1975034569
Cited by
174
References
1
FWCI
3.98
Type
journal article
Language
en
Open access
green

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: Analysis of endoplasmic reticulum trafficking signals by combinatorial screening in mammalian cells. https://app.cochat.ai/papers/10.1073/pnas.051630198
The paper
Zerangue, N., Malan, M. J., Fried, S. R., Dazin, P. F., Jan, Y. N., Jan, L. Y., & Schwappach, B. (2001). Analysis of endoplasmic reticulum trafficking signals by combinatorial screening in mammalian cells. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.051630198

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.