Branch prioritization motifs in biochemical networks with sharp activation
Bibliographic record
Abstract
The Precursor Shutoff Valve (PSV) has been proposed as a motif in biochemical networks, active for example in prioritization of primary over secondary metabolism in plants in low-input conditions. Another branch prioritization mechanism in a biochemical network is a difference in thresholds for activation of the two pathways from the branch point. It has been shown by Adams and colleagues that both mechanisms can play a part in a model of plant metabolism involving Michaelis-Menten kinetics [ 1 ]. Here we investigate the potential role of these two mechanisms in systems with steeper activation functions, such as those involving highly cooperative reactions, by considering the limit of infinitely steep activation functions, as is done in Glass networks as models of gene regulation. We find that the Threshold Separation mechanism is completely effective in pathway prioritization in such a model framework, while the PSV adds no additional benefit, and is ineffective on its own. This makes clear that the PSV uses the gradual nature of activation functions to help shut off one branch at low input levels, and has no effect if activation is sharp. The analysis also serves as a case study in assessing behaviour of sharply-switching open systems without degradation of species.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".