Impacts of protein–protein interaction domains on organism and network complexity
Bibliographic record
Abstract
It has been a puzzle that genome or proteome sizes are not correlated with the complexity of the organisms. Although alternative splicing and noncoding and regulatory elements explain some of the differences, the complexity of the protein interaction network and regulatory network may provide additional explanations. Here, we collected 642 domains that mediate protein-protein interactions (PPIs) and examined the evolution of the PPI domains and its impact on organismal complexity and PPI network complexity. In agreement with previous more general studies of protein domains, a significant expansion of PPI domains per proteome was found in metazoa. We also found both the number and coverage of PPI domains per protein increased. However, a better correlation with complexity was seen with increasing PPI domain coverage per protein, so that proteins in complex organisms are more compact and specialized in PPI. Such a structural adaptation of the proteins is correlated with the number of interactions that the proteins can make in PPI networks, and seems to be a more favorable way to increase network connectivity than other structural adaptations.
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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 | 0.001 | 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".