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Record W1981812984 · doi:10.12703/p5-30

Novel methods for studying multiprotein complexes in vivo

2013· article· en· W1981812984 on OpenAlexafffund
Virja Mehta, Laura Trinkle‐Mulcahy

Bibliographic record

VenueF1000Prime Reports · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiotin and Related Studies
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchTerry Fox Foundation
KeywordsComputational biologyIn vivoProteomicsMultiprotein complexProtein–protein interactionCell biologyEpitopeChemistryBiologyBiophysicsBiochemistryGeneticsGeneAntibody

Abstract

fetched live from OpenAlex

The current consensus is that the majority of proteins act in concert in the cell, as homo- and heteromeric complexes of two or more proteins that carry out discrete biological functions. A wide range of genomic, proteomic, biochemical, structural and biophotonic techniques have been employed over the years to study the protein-protein interactions that define complexes, with the end goal of producing a spatiotemporal map of these modular functional units throughout the cell. Recent advances in the analysis of in vivo complexes have greatly improved structural, functional and temporal resolution, and this review highlights novel approaches ranging from proximity-dependent labeling and cross-linking/mass spectrometry through pulse-chase epitope labeling and targeted protein degradation.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.004

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 head0.028
GPT teacher head0.333
Teacher spread0.306 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations4
Published2013
Admission routes2
Has abstractyes

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