WMP: A novel comprehensive wheat miRNA database, including related bioinformatics software
Bibliographic record
Abstract
Abstract MicroRNAs (miRNAs) are emerging as important post tran-scriptional regulators that may regulate key plant genes responsible for agronomic traits such as grain yield and stress tolerance. Several studies identified species and clades specific miRNA families associated with plant stress regulated genes. Here, we propose a novel resource that provides data related to the expression of abiotic stress responsive miRNAs in wheat, one of the most important staple food crops. This database allows the query of small RNA libraries, including in silico predicted wheat miRNA sequences and the expression profiles of small RNAs identified from those libraries. Our database also provides a direct access to online miRNA prediction software tuned to de novo miRNA detection in wheat, in monocotyledon clades, as well as in other plant species. These data and software will facilitate multiple comparative analyses and reproducible studies on small RNAs and miRNA families in plants. Our web-portal is available at: http://wheat.bioinfo.uqam.ca .
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.024 |
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".