Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,104

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

A DNA vector-based RNAi technology to suppress gene expression in mammalian cells

Open access
Sui, Guangchao, Soohoo, Christina, Affar, El Bachir, Gay, Frédérique, Shi, Yujiang, Forrester, William C., Shi, Yang·2002·Proceedings of the National Academy of Sciences

Abstract

Double-stranded RNA-mediated interference (RNAi) has recently emerged as a powerful reverse genetic tool to silence gene expression in multiple organisms including plants, Caenorhabditis elegans , and Drosophila . The discovery that synthetic double-stranded, 21-nt small interfering RNA triggers gene-specific silencing in mammalian cells has further expanded the utility of RNAi into mammalian systems. Here we report a technology that allows synthesis of small interfering RNAs from DNA templates in vivo to efficiently inhibit endogenous gene expression. Significantly, we were able to use this approach to demonstrate, in multiple cell lines, robust inhibition of several endogenous genes of diverse functions. These findings highlight the general utility of this DNA vector-based RNAi technology in suppressing gene expression in mammalian cells.

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.082117599

Cites

3 of 3 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

Show all 3 references

Cited by

See all 1,104

Metadata

Authors
Sui, G., Soohoo, C., Affar, E. B., Gay, F., Shi, Y., Forrester, W. C., & Shi, Y.
Venue
Proceedings of the National Academy of Sciences
Published
2002-04-16
Volume
99
Issue
8
Pages
5515-5520
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2146900615
Cited by
1,104
References
3
FWCI
54.00
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: A DNA vector-based RNAi technology to suppress gene expression in mammalian cells. https://app.cochat.ai/papers/10.1073/pnas.082117599
The paper
Sui, G., Soohoo, C., Affar, E. B., Gay, F., Shi, Y., Forrester, W. C., & Shi, Y. (2002). A DNA vector-based RNAi technology to suppress gene expression in mammalian cells. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.082117599

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.