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Record W2793688464 · doi:10.1039/c7mo00142h

Systems analysis of the genetic interaction network of yeast molecular chaperones

2018· article· en· W2793688464 on OpenAlexafffund
Kamran Rizzolo, Ashwani Kumar, Yoshito Kakihara, Sadhna Phanse, Zoran Minić, Jamie Snider, Igor Štagljar, Sandra Zilles, Mohan Babu, Walid A. Houry

Bibliographic record

VenueMolecular Omics · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsUniversity of ReginaUniversity of TorontoToronto Public Health
FundersNational Safety Academic FundCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsYeastComputational biologyBiologyGenetics

Abstract

fetched live from OpenAlex

Molecular chaperones are typically promiscuous interacting proteins that function globally in the cell to maintain protein homeostasis. Recently, we had carried out experiments that elucidated a comprehensive interaction network for the core 67 chaperones and 15 cochaperones in the budding yeast Saccharomyces cerevisiae [Rizzolo et al., Cell Rep., 2017, 20, 2735-2748]. Here, the genetic (i.e. epistatic) interaction network obtained for chaperones was further analyzed, revealing that the global topological parameters of the resulting network have a more central role in mediating interactions in comparison to the rest of the proteins in the cell. Most notably, we observed Hsp10, Hsp70 Ssz1 chaperone, and Hsp90 cochaperone Cdc37 to be the main drivers of the network architecture. Systematic analysis on the physicochemical properties for all chaperone interactors further revealed the presence of preferential domains and folds that are highly interactive with chaperones such as the WD40 repeat domain. Further analysis with established cellular complexes revealed the involvement of R2TP chaperone in quaternary structure formation. Our results thus provide a global overview of the chaperone network properties in yeast, expanding our understanding of their functional diversity and their role in protein homeostasis.

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 score0.134
Threshold uncertainty score0.468

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 head0.005
GPT teacher head0.215
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

Citations15
Published2018
Admission routes2
Has abstractyes

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