TRANSNAP: a web database providing comprehensive information on Japanese pear transcriptome
Bibliographic record
Abstract
Japanese pear (Pyrus pyrifolia) is a major fruit tree in the family Rosaceae and is bred for fruit production. To promote the development of breeding strategies and molecular research for Japanese pear, we sequenced the transcripts of Japanese pear variety 'Hosui'. To exhaustively collect information of total gene expression, RNA samples from various organs and stages of Japanese pear were sequenced by three technologies, single-molecule real-time (SMRT) sequencing, 454 pyrosequencing, and Sanger sequencing. Using all those reads, we determined comprehensive reference sequences of Japanese pear. Then, their protein sequences were predicted, and biological functional annotations were assigned. Finally, we developed a web database, TRANSNAP (http://plantomics.mind.meiji.ac.jp/nashi), which is the first web resource of Japanese pear omics information. This database provides highly reliable information via a user-friendly web interface: the reference sequences, gene functional annotations, and gene expression profiles from microarray experiments. In addition, based on sequence comparisons among Japanese, Chinese and European pears, similar protein sequences among the pears and species-specific proteins in Japanese pear can be quickly and efficiently identified. TRANSNAP will aid molecular research and breeding in Japanese pear, and its information is available for comparative analysis among other pear species and families.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".