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Cited by 226

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Id proteins control growth induction in mammalian cells.

Open access
Barone, M V, Pepperkok, R, Peverali, F A, Philipson, L·1994·Proceedings of the National Academy of Sciences

Abstract

Id1, Id2, and Id3 (HLH462) dimerize with members of the basic helix-loop-helix protein family, but due to the absence of the basic region, the resulting heterodimers cannot bind DNA. Therefore Id-type proteins negatively regulate DNA binding of the basic helix-loop-helix proteins. Here we report that Id1, Id2, and Id3 are induced shortly after serum stimulation in arrested NIH 3T3. Antisense oligonucleotides against the Id mRNAs delay the reentry of arrested cells into the cell cycle elicited by stimulation with serum or growth factors. Antisense oligonucleotides against all three Id mRNAs are more effective than individual ones. Combined, these results indicate that Id proteins are involved in the control of growth induction.

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Crossref · 10.1073/pnas.91.11.4985

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Metadata

Authors
Barone, M. V., Pepperkok, R., Peverali, F. A., & Philipson, L.
Venue
Proceedings of the National Academy of Sciences
Published
1994-05-24
Volume
91
Issue
11
Pages
4985-4988
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2109663412
Cited by
226
References
2
FWCI
4.78
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Id proteins control growth induction in mammalian cells. https://app.cochat.ai/papers/10.1073/pnas.91.11.4985
The paper
Barone, M. V., Pepperkok, R., Peverali, F. A., & Philipson, L. (1994). Id proteins control growth induction in mammalian cells. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.91.11.4985

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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.