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Record W2008897692 · doi:10.1002/pmic.201000039

Expanding the mouse embryonic stem cell proteome: Combining three proteomic approaches

2010· article· en· W2008897692 on OpenAlexfundno aff
Rebekah L. Gundry, Irina Tchernyshyov, Shijun Sheng, Yelena S. Tarasova, Kimberly Raginski, Kenneth R. Boheler, Jennifer E. Van Eyk

Bibliographic record

VenuePROTEOMICS · 2010
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchU.S. Public Health ServiceNational Institutes of Health
KeywordsProteomeEmbryonic stem cellProteomicsGene isoformBiologyInduced pluripotent stem cellCell biologyProtein isoformPeptideCell cultureStem cellCellMolecular biologyComputational biologyBiochemistryGeneticsGene

Abstract

fetched live from OpenAlex

The current study used three different proteomic strategies, which differed by their extent of intact protein separation, to examine the proteome of a pluripotent mouse embryonic stem cell line, R1. Proteins from whole-cell lysates were subjected either to 2-D-LC, or 1-DE, or were unfractionated prior to enzymatic digestion and subsequent analysis by MS. The results yielded 1895 identified non-redundant proteins and, for 128 of these, the specific isoform could be determined based on detection of an isoform-specific peptide. When compared with two previously published proteomic studies that used the same cell line, the current study reveals 612 new proteins.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.254
Teacher spread0.224 · 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

Citations19
Published2010
Admission routes1
Has abstractyes

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