Deciphering RNA Regulatory Elements Involved in the Developmental and Environmental Gene Regulation of Trypanosoma brucei
Bibliographic record
Abstract
Trypanosoma brucei is a vector-borne parasite with intricate life cycle that can cause serious diseases in humans and animals. This pathogen relies on fine regulation of gene expression to respond and adapt to variable environments, with implications in transmission and infectivity. However, the involved regulatory elements and their mechanisms of actions are largely unknown. Here, benefiting from a new graph-based approach for finding functional regulatory elements in RNA (GRAFFER), we have predicted 88 new RNA regulatory elements that are potentially involved in the gene regulatory network of T. brucei. We show that many of these newly predicted elements are responsive to both transcriptomic and proteomic changes during the life cycle of the parasite. Moreover, we found that 11 of predicted elements strikingly resemble previously identified regulatory elements for the parasite. Additionally, comparison with previously predicted motifs on T. brucei suggested the superior performance of our approach based on the current limited knowledge of regulatory elements in T. brucei.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".