MétaCan
Menu
Back to cohort
Record W1978303592 · doi:10.1371/journal.pone.0000249

Control of Signaling in a MAP-kinase Pathway by an RNA-Binding Protein

2007· article· en· W1978303592 on OpenAlexafffund
Susanne Prinz, Christine Aldridge, Stephen A. Ramsey, R. J. Taylor, Timothy Galitski

Bibliographic record

VenuePLoS ONE · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesNational Institutes of HealthMichael Smith Health Research BC
Keywordsc-RafCell biologyRNA-binding proteinBiologyASK1MAP3K7Cyclin-dependent kinase 9MAP2K7MAPKAPK2Signal transductionMAP kinase kinase kinaseMitogen-activated protein kinase kinaseProtein kinase ARNACyclin-dependent kinase 2GeneticsKinaseGene

Abstract

fetched live from OpenAlex

Signaling-protein mRNAs tend to have long untranslated regions (UTRs) containing binding sites for RNA-binding proteins regulating gene expression. Here we show that a PUF-family RNA-binding protein, Mpt5, represses the yeast MAP-kinase pathway controlling differentiation to the filamentous form. Mpt5 represses the protein levels of two pathway components, the Ste7 MAP-kinase kinase and the Tec1 transcriptional activator, and negatively regulates the kinase activity of the Kss1 MAP kinase. Moreover, Mpt5 specifically inhibits the output of the pathway in the absence of stimuli, and thereby prevents inappropriate cell differentiation. The results provide an example of what may be a genome-scale level of regulation at the interface of signaling networks and protein-RNA binding networks.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.021
GPT teacher head0.247
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations20
Published2007
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicRNA Research and SplicingFrench-language works237,207