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Record W2131525103 · doi:10.1039/c3mb70599d

High-content screening of yeast mutant libraries by shotgun lipidomics

2014· article· en· W2131525103 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMolecular BioSystems · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsUniversité de Montréal
FundersDanmarks Frie ForskningsfondLundbeckfondenNatur og Univers, Det Frie Forskningsråd
KeywordsLipidomicsYeastShotgunMutantOrbitrapSaccharomyces cerevisiaeMetabolomicsComputational biologyHigh-throughput screeningBiologyGenetic screenLipid metabolismBiochemistryChemistryMass spectrometryGeneBioinformaticsChromatography

Abstract

fetched live from OpenAlex

To identify proteins with a functional role in lipid metabolism and homeostasis we designed a high-throughput platform for high-content lipidomic screening of yeast mutant libraries. To this end, we combined culturing and lipid extraction in 96-well format, automated direct infusion nanoelectrospray ionization, high-resolution Orbitrap mass spectrometry, and a dedicated data processing framework to support lipid phenotyping across hundreds of Saccharomyces cerevisiae mutants. Our novel approach revealed that the absence of genes with unknown function YBR141C and YJR015W, and the transcription factor KAR4 precipitated distinct lipid metabolic phenotypes. These results demonstrate that the high-throughput shotgun lipidomics platform is a valid and complementary proxy for high-content screening of yeast mutant libraries.

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.

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 score0.044
Threshold uncertainty score0.915

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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