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Record W2118655754 · doi:10.1091/mbc.e04-03-0167

Cold Adaptation in Budding Yeast

2004· article· en· W2118655754 on OpenAlexafffund
Babette Schade, Gregor Jansen, Malcolm Whiteway, K.-D. Entian, David Y. Thomas

Bibliographic record

VenueMolecular Biology of the Cell · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFungal and yeast genetics research
Canadian institutionsMcGill UniversityBiotechnology Research InstituteRoyal Victoria Hospital
FundersLallemand
KeywordsBiologySaccharomyces cerevisiaeGeneCold stressFight-or-flight responseCell biologyGeneticsDNA damageGene expressionDNA

Abstract

fetched live from OpenAlex

We have determined the transcriptional response of the budding yeast Saccharomyces cerevisiae to cold. Yeast cells were exposed to 10 degrees C for different lengths of time, and DNA microarrays were used to characterize the changes in transcript abundance. Two distinct groups of transcriptionally modulated genes were identified and defined as the early cold response and the late cold response. A detailed comparison of the cold response with various environmental stress responses revealed a substantial overlap between environmental stress response genes and late cold response genes. In addition, the accumulation of the carbohydrate reserves trehalose and glycogen is induced during late cold response. These observations suggest that the environmental stress response (ESR) occurs during the late cold response. The transcriptional activators Msn2p and Msn4p are involved in the induction of genes common to many stress responses, and we show that they mediate the stress response pattern observed during the late cold response. In contrast, classical markers of the ESR were absent during the early cold response, and the transcriptional response of the early cold response genes was Msn2p/Msn4p independent. This implies that the cold-specific early response is mediated by a different and as yet uncharacterized regulatory mechanism.

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 score0.004
Threshold uncertainty score0.265

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 head0.010
GPT teacher head0.255
Teacher spread0.245 · 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

Citations176
Published2004
Admission routes2
Has abstractyes

Explore more

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