MétaCan
Menu
Back to cohort
Record W2083164724 · doi:10.1139/g10-029

Reexamining the DNA target selectivity of Scalloped

2010· article· en· W2083164724 on OpenAlexaffvenue
Abhishek D. Garg, John B. Bell

Bibliographic record

VenueGenome · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEnhancerBiologyTranscription factorDNAGeneDNA-binding proteinTranscription (linguistics)Cell biologyCofactorRegulation of gene expressionGeneticsBiochemistryEnzyme

Abstract

fetched live from OpenAlex

Selector proteins are transcription factors that coordinate the formation and identity of organs and appendages. The proper formation of these tissues requires the selector proteins to regulate the expression of a large set of genes. Many selector proteins are involved in regulating multiple developmental processes, yet it is not completely clear how they are able to activate different sets of genes in a tissue-specific manner. An association with cofactors is thought to be one method by which enhancer selectivity is achieved. During wing development the selector protein Scalloped (SD) interacts with the cofactor Vestigial (VG). This interaction leads to the activation of a specific set of downstream wing genes. Herein, data are presented indicating that the switch in binding selectivity is likely achieved by VG altering the general affinity that the SD protein has for DNA. The decreased affinity for DNA is compensated for by the fact that the VG protein forms a complex containing two SD proteins. These two properties ensure that the SD-VG complex is able to bind only to enhancers that have two consecutive binding sites. Furthermore, data are presented that indicate that the function of the two terminal domains of the VG protein is not restricted to activating transcription and promoting the recruitment of two SD 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 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 score0.384
Threshold uncertainty score0.168

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 head0.005
GPT teacher head0.214
Teacher spread0.209 · 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 teacher head, 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

Citations4
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueGenomeSame topicDevelopmental Biology and Gene RegulationFrench-language works237,207