FINDING CONSERVED WELL-ORDERED RNA STRUCTURES IN GENOMIC SEQUENCES
Why this work is in the frame
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Bibliographic record
Abstract
Recent advances in RNA studies show that the well-ordered, structured RNAs perform a broad functions in various biological mechanisms. Included among these functions are regulations of gene expression at multiple levels by diversified ribozymes and various RNA regulatory elements. The discovered microRNAs (miRNAs) with a distinct stem-loops are a new class of RNA regulatory elements. The prediction of those well-ordered folding sequences (WFS) associated with the RNA regulatory elements in genomic sequences is very helpful for our understandings of RNA-based gene regulations. We present here a new computational method in searching for the conserved WFS in genomes. In the method, the WFS is assessed by a quantitative measure E diff that is defined as the difference of free energies between the computed optimal structure (OS) and its corresponding optimal restrained structure where all the previous base pairings in the OS are forbidden. From those WFS with high E diff scores, the conserved WFS is determined by computing the maximal similarity score (MSS) between the two compared structures. In practice, we first search for those distinct WFS with high statistical significance in genomic sequences and then seek for those conserved WFS with high MSS. The potential and implications of our discoveries in the genome of Caenorhabditis elegans are discussed.
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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