FuNTAP: A Fusarium graminearum Protein-Protein Interaction Network to Study Deoxynivalenol Biosynthesis Pathways
Bibliographic record
Abstract
Protein interaction networks provide invaluable information on the complexity of biological pathways within organisms. These networks help identify proteins of interest along with groups of closely associated proteins with common functions. The fungus Fusarium graminearum is a pathogen of agriculturally significant crops such as wheat. The infection process includes production of harmful mycotoxins such as deoxynivalenol (DON). To study the signalling pathways leading to biosynthesis of DON in F. graminearum, we constructed the Fusarium Network of Trichothecene Associated Proteins (FuNTAP) based on yeast two-hybrid interactions of proteins differentially expressed under DON inducing conditions. The FuNTAP network categorizes the metabolic pathway which produces this important mycotoxin without the drawbacks of previous predicted-based model interactomes. As such, we present the FuNTAP network as a tool to identify proteins regulating the biosynthesis of DON. This network may also integrate other sources of data including gene expression profiles and biological function through sequence similarity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".