YMDB 2.0: a significantly expanded version of the yeast metabolome database
Bibliographic record
Abstract
YMDB or the Yeast Metabolome Database (http://www.ymdb.ca/) is a comprehensive database containing extensive information on the genome and metabolome of Saccharomyces cerevisiae Initially released in 2012, the YMDB has gone through a significant expansion and a number of improvements over the past 4 years. This manuscript describes the most recent version of YMDB (YMDB 2.0). More specifically, it provides an updated description of the database that was previously described in the 2012 NAR Database Issue and it details many of the additions and improvements made to the YMDB over that time. Some of the most important changes include a 7-fold increase in the number of compounds in the database (from 2007 to 16 042), a 430-fold increase in the number of metabolic and signaling pathway diagrams (from 66 to 28 734), a 16-fold increase in the number of compounds linked to pathways (from 742 to 12 733), a 17-fold increase in the numbers of compounds with nuclear magnetic resonance or MS spectra (from 783 to 13 173) and an increase in both the number of data fields and the number of links to external databases. In addition to these database expansions, a number of improvements to YMDB's web interface and its data visualization tools have been made. These additions and improvements should greatly improve the ease, the speed and the quantity of data that can be extracted, searched or viewed within YMDB. Overall, we believe these improvements should not only improve the understanding of the metabolism of S. cerevisiae, but also allow more in-depth exploration of its extensive metabolic networks, signaling pathways and biochemistry.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.051 | 0.080 |
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".