e-RNA: a collection of web servers for comparative RNA structure prediction and visualisation
Bibliographic record
Abstract
e-RNA offers a free and open-access collection of five published RNA sequence analysis tools, each solving specific problems not readily addressed by other available tools. Given multiple sequence alignments, Transat detects all conserved helices, including those expected in a final structure, but also transient, alternative and pseudo-knotted helices. RNA-Decoder uses unique evolutionary models to detect conserved RNA secondary structure in alignments which may be partly protein-coding. SimulFold simultaneously co-estimates the potentially pseudo-knotted conserved structure, alignment and phylogenetic tree for a set of homologous input sequences. CoFold predicts the minimum-free energy structure for an input sequence while taking the effects of co-transcriptional folding into account, thereby greatly improving the prediction accuracy for long sequences. R-chie is a program to visualise RNA secondary structures as arc diagrams, allowing for easy comparison and analysis of conserved base-pairs and quantitative features. The web site server dispatches user jobs to a cluster, where up to 100 jobs can be processed in parallel. Upon job completion, users can retrieve their results via a bookmarked or emailed link. e-RNA is located at http://www.e-rna.org.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.071 | 0.103 |
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".