Functional annotation of the <i>Arabidopsis</i> P450 superfamily based on large-scale co-expression analysis
Bibliographic record
Abstract
Cytochrome P450 mono-oxygenases play prominent roles in a diverse set of metabolic pathways, but the function of most of these enzymes remains obscure. A bottleneck in the functional genomics of this superfamily constitutes hypothesis generation to identify potential substrates (or substrate classes) individual P450s may act on. We used publicly available large-scale expression data to perform co-expression analysis comparing the expression matrix of each P450 with those from more than 4000 selected genes across thousands of microarrays. Based on functional annotations of co-expressed genes from a diverse set of databases, co-expressed pathways were thus identified for each P450. Using this approach, most P450s with known functions were placed into their respective pathways, thereby proofing the concept. As examples, pathway mapping results identifying novel P450s potentially acting on flower-specific monoterpenes and root-specific triterpenes are described. Co-expression results for all Arabidopsis P450s will be presented as a web resource on the 'CYPedia' web pages (http://ibmp.u-strasbg.fr/CYPedia/).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".