Mapping functional associations in the entire genome of <i>Drosophila melanogaster</i> using fusion analysis
Why this work is in the frame
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Bibliographic record
Abstract
We have previously shown that the detection of gene fusion events can contribute towards the elucidation of functional associations of proteins within entire genomes. Here we have analysed the entire genome of Drosophila melanogaster using fusion analysis and two additional constraints that improve the reliability of the predictions, viz. low sequence similarity and low degree of paralogy of the component proteins involved in a fusion event. Imposing these constraints, the total number of unique component pairs is reduced from 18 654 to a mere 220 cases, which are expected to represent some of the most reliably detected functionally associated proteins. Using additional information from sequence databases, we have been able to detect pairs of functionally associated proteins with important functions in cellular and developmental pathways, such as spermatogenesis and programmed cell death.
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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 | 0.000 | 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) | 0.000 | 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 it