Generally applicable transcriptome-wide analysis of translation using anota2seq
Bibliographic record
Abstract
mRNA translation plays an evolutionarily conserved role in homeostasis and when dysregulated contributes to various disorders including metabolic and neurological diseases and cancer. Notwithstanding that optimal and universally applicable methods are critical for understanding the complex role of translational control under physiological and pathological conditions, approaches to analyze translatomes are largely underdeveloped. To address this, we developed the anota2seq algorithm which outperforms current methods for statistical identification of changes in translation. Notably, in contrast to available analytical methods, anota2seq also allows specific identification of an underappreciated mode of gene expression regulation whereby translation acts as a buffering mechanism which maintains protein levels despite fluctuations in corresponding mRNA abundance ('translational buffering'). Thus, the universal anota2seq algorithm allows efficient and hitherto unprecedented interrogation of translatomes which is anticipated to advance knowledge regarding the role of translation in homeostasis and disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".