MétaCan
Menu
Back to cohort

Chaperoning the Proteome

2017· article· en· W4389022669 on OpenAlexafffundabout
Walid A. Houry

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsChaperone (clinical)Co-chaperoneProteomeHsp90Saccharomyces cerevisiaeBiologyCell biologyCDC37Computational biologyHeat shock proteinGeneticsYeastGene

Abstract

fetched live from OpenAlex

Molecular chaperones are critical to maintaining cellular protein homeostasis. There are several families of chaperones in the cell with some being specific for certain substrates, while others act on many protein targets. As a result, chaperones are expected to be involved in many cellular pathways with only a few being well elucidated. To obtain a comprehensive view of chaperone function in the cell, we developed an integrative approach based on systematic physical and genetic interaction mapping to decipher interactions involving all main chaperones (67) and cochaperones (15) of Saccharomyces cerevisiae . The analysis revealed novel chaperone substrates and novel chaperone activities. As part of this analysis, we unexpectedly found that many interactors of the Hsp90 chaperone system are proteins that form foci under stress conditions. Such foci forming tendency was then demonstrated for the highly conserved AAA+ ATPases Rvb1 and Rvb2 that are part of the R2TP complex that interacts with Hsp90. In response to nutrient deprivation, a fraction of Rvb1 and Rvb2 colocalize to perinuclear foci that dissolve upon nutrient addition. We propose that foci formation might be a feature of many chaperone substrates. Support or Funding Information Canadian Institutes of Health Research

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 score0.003
Threshold uncertainty score0.010

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.029
GPT teacher head0.312
Teacher spread0.283 · 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

Citations0
Published2017
Admission routes3
Has abstractyes

Explore more

Same venueThe FASEB JournalSame topicHeat shock proteins researchFrench-language works237,207