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High-Throughput Integrated Analyses for the Tyrosinase-Induced Melanogenesis: Microarray, Proteomics and Interactomics Studies

2010· article· en· W2063207851 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

VenueJournal of Biomolecular Structure and Dynamics · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsGeneProteomicsMicroarrayComputational biologyTyrosinaseBiologyDNA microarrayProtein–protein interactionMicroarray analysis techniquesGene expressionMolecular biologyGeneticsBiochemistryEnzyme

Abstract

fetched live from OpenAlex

The tyrosinase gene was overexpressed in HEK293 cells, and then a DNA microarray and proteomic tools were applied to detect the dysregulated genes in highly pigmented cells. The candidate genes from the microarray were compared to the yeast two-hybridization results. Computational prediction via protein-protein interaction mapping suggested the existence of 66 hub genes in melanogenesis. Most importantly, RNA binding motif protein 9 is newly detected as a putative critical melanogenesis-associated gene in this study. The approach of combining the expression data analysis and predicted protein interaction partners performed in large scales can bring more reliable gene targets for understanding pigmentation.

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 score0.015
Threshold uncertainty score0.450

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 head0.019
GPT teacher head0.329
Teacher spread0.310 · 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