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Record W1983736629 · doi:10.1016/j.celrep.2015.01.052

A Cell-Signaling Network Temporally Resolves Specific versus Promiscuous Phosphorylation

2015· article· en· W1983736629 on OpenAlexafffund
Evgeny Kanshin, Louis-Philippe Bergeron-Sandoval, Pierre Thibault, Stephen W. Michnick

Bibliographic record

VenueCell Reports · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversité du Québec à MontréalUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersCanadian Institutes of Health ResearchSyddansk Universitet
KeywordsPhosphorylationCell biologySignal transductionCellCell signalingComputational biologyBiologyChemistryBiochemistry

Abstract

fetched live from OpenAlex

If specific and functional kinase- or phosphatase-substrate interactions are optimized for binding compared to promiscuous interactions, then changes in phosphorylation should occur faster on functional versus promiscuous substrates. To test this hypothesis, we designed a high temporal resolution global phosphoproteomics protocol to study the high-osmolarity glycerol (HOG) response in the budding yeast Saccharomyces cerevisiae. The method provides accurate, stimulus-specific measurement of phosphoproteome changes, quantitative analysis of phosphodynamics at sub-minute temporal resolution, and detection of more phosphosites. Rates of evolution of dynamic phosphosites were comparable to those of known functional phosphosites and significantly lower than static or longer-time-frame dynamic phosphosites. Kinetic profile analyses indicated that putatively functional kinase- or phosphatase-substrate interactions occur more rapidly, within 60 s, than promiscuous interactions. Finally, we report many changes in phosphorylation of proteins implicated in cytoskeletal and mitotic spindle dynamics that may underlie regulation of cell cycle and morphogenesis.

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)0.001
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 score0.152
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.030
GPT teacher head0.240
Teacher spread0.210 · 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

Citations96
Published2015
Admission routes2
Has abstractyes

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