Wheat EST sequence assembly facilitates comparison of gene contents among plant species and discovery of novel genes
Bibliographic record
Abstract
Using a strategy requiring only modest computational resources, wheat expressed sequence tag (EST) sequences from various sources were assembled into contigs and compared with a nonredundant barley sequence assembly, with ESTs, with complete draft genome sequences of rice and Arabidopsis thaliana, and with ESTs from other plant species. These comparisons indicate that (i) wheat sequences available from public sources represent a substantial proportion of the diversity of wheat coding sequences, (ii) prediction of open reading frames in the whole genome sequence improves when supplemented with EST information from other species, (iii) a substantial number of candidates for novel genes that are unique to wheat or related species can be identified, and (iv) a smaller number of genes can be identified that are common to monocots and dicots but absent from Arabidopsis. The sequences in the last group may have been lost from Arabidopsis after descendance from a common ancestor. Examples of potential novel wheat genes and Triticeae-specific genes are presented.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".