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Record W1944550764 · doi:10.25011/cim.v30i4.2858

Spatial localization of unknown proteins in the endoplasmic reticulum predicts functions

2007· article· en· W1944550764 on OpenAlexvenueno aff
Michael D. Jain, Hisao Nagaya, Annalyn Gilchrist, Mirosław Cygler, John Bergeron

Bibliographic record

VenueClinical and investigative medicine · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsnot available
Fundersnot available
KeywordsEndoplasmic reticulumProteomicsCell biologyRibosomeMembrane proteinSec61Protein foldingFunction (biology)CytosolFolding (DSP implementation)BiologyChemistryBiophysicsMembraneTransloconBiochemistryRNA

Abstract

fetched live from OpenAlex

Protein synthesis, folding and degradation functions are spatially segregated in the endoplasmic reticulum (ER) with respect to the membrane and the ribosome (rough and smooth ER). Interrogation of a proteomics resource characterizing rough and smooth ER membranes subfractionated into cytosolic, membrane, and soluble fractions gives a spatial map of known proteins involved in ER function. The spatial localization of 224 identified unknown proteins in the ER is predicted to give insight into their function. Here we provide evidence that the proteomics resource accurately predicts the function of new proteins involved in protein synthesis (nudilin), protein translocation across the ER membrane (nicalin), co-translational protein folding (stexin), and distal protein folding in the lumen of the ER (erlin-1, TMX2). Proteomics provides the spatial localization of proteins and can be used to accurately predict protein function.

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)0.001
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: 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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.052
GPT teacher head0.288
Teacher spread0.236 · 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
Published2007
Admission routes1
Has abstractyes

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