How affinity of the ELT-2 GATA factor binding to <i>cis-</i>acting regulatory sites controls <i>Caenorhabditis elegans</i> intestinal gene transcription
Bibliographic record
Abstract
ABSTRACT We define a quantitative relationship between the affinity with which the intestine-specific GATA factor ELT-2 binds to cis-acting regulatory motifs and the resulting transcription of asp-1, a target gene representative of genes involved in Caenorhabditis elegans intestine differentiation. By establishing an experimental system that allows unknown parameters (e.g. the influence of chromatin) to effectively cancel out, we show that levels of asp-1 transcripts increase monotonically with increasing binding affinity of ELT-2 to variant promoter TGATAA sites. The shape of the response curve reveals that the product of the unbound ELT-2 concentration in vivo [i.e. (ELT-2free) or ELT-2 ‘activity’] and the largest ELT-XXTGATAAXX association constant (Kmax) lies between five and ten. We suggest that this (unitless) product [Kmax×(ELT-2free) or the equivalent product for any other transcription factor] provides an important quantitative descriptor of transcription-factor/regulatory-motif interaction in development, evolution and genetic disease. A more complicated model than simple binding affinity is necessary to explain the fact that ELT-2 appears to discriminate in vivo against equal-affinity binding sites that contain AGATAA instead of TGATAA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".