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Record W2141488967 · doi:10.1091/mbc.e06-04-0368

A Survey of Essential Gene Function in the Yeast Cell Division Cycle

2006· article· en· W2141488967 on OpenAlexafffund
Lisa Yu, Lourdes Peña‐Castillo, Sanié Mnaimneh, Timothy R. Hughes, Grant W. Brown

Bibliographic record

VenueMolecular Biology of the Cell · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFungal and yeast genetics research
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchNational Cancer InstituteGenome Canada
KeywordsBiologyCell cycleGeneCell divisionDNA replicationGeneticsMutantFunction (biology)Cell biologyMutationCell

Abstract

fetched live from OpenAlex

Mutations impacting specific stages of cell growth and division have provided a foundation for dissecting mechanisms that underlie cell cycle progression. We have undertaken an objective examination of the yeast cell cycle through flow cytometric analysis of DNA content in TetO(7) promoter mutant strains representing 75% of all essential yeast genes. More than 65% of the strains displayed specific alterations in DNA content, suggesting that reduced function of an essential gene in most cases impairs progression through a specific stage of the cell cycle. Because of the large number of essential genes required for protein biosynthesis, G1 accumulation was the most common phenotype observed in our analysis. In contrast, relatively few mutants displayed S-phase delay, and most of these were defective in genes required for DNA replication or nucleotide metabolism. G2 accumulation appeared to arise from a variety of defects. In addition to providing a global view of the diversity of essential cellular processes that influence cell cycle progression, these data also provided predictions regarding the functions of individual genes: we identified four new genes involved in protein trafficking (NUS1, PHS1, PGA2, PGA3), and we found that CSE1 and SMC4 are important for DNA replication.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.243
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations111
Published2006
Admission routes2
Has abstractyes

Explore more

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