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Cited by 768

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

Systematic Identification of Pathways That Couple Cell Growth and Division in Yeast

Jorgensen, Paul, Nishikawa, Joy L., Breitkreutz, Bobby-Joe, Tyers, Mike·2002·Science

Abstract

Size homeostasis in budding yeast requires that cells grow to a critical size before commitment to division in the late prereplicative growth phase of the cell cycle, an event termed Start. We determined cell size distributions for the complete set of ∼6000 Saccharomyces cerevisiae gene deletion strains and identified ∼500 abnormally small ( whi ) or large ( lge ) mutants. Genetic analysis revealed a complex network of newly found factors that govern critical cell size at Start, the most potent of which were Sfp1, Sch9, Cdh1, Prs3, and Whi5. Ribosome biogenesis is intimately linked to cell size through Sfp1, a transcription factor that controls the expression of at least 60 genes implicated in ribosome assembly. Cell growth and division appear to be coupled by multiple conserved mechanisms.

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Crossref · 10.1126/science.1070850

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Metadata

Authors
Jorgensen, P., Nishikawa, J. L., Breitkreutz, B.-J., & Tyers, M.
Venue
Science
Published
2002-07-19
Volume
297
Issue
5580
Pages
395-400
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2088127501
Cited by
768
References
3
FWCI
14.04
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Systematic Identification of Pathways That Couple Cell Growth and Division in Yeast. https://app.cochat.ai/papers/10.1126/science.1070850
The paper
Jorgensen, P., Nishikawa, J. L., Breitkreutz, B.-J., & Tyers, M. (2002). Systematic Identification of Pathways That Couple Cell Growth and Division in Yeast. Science. https://doi.org/10.1126/science.1070850

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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.