Analyses of<i> Physcomitrella patens</i> Ankyrin Repeat Proteins by Computational Approach
Bibliographic record
Abstract
Ankyrin (ANK) repeat containing proteins are evolutionary conserved and have functions in crucial cellular processes like cell cycle regulation and signal transduction. In this study, through an entirely in silico approach using the first release of the moss genome annotation, we found that at least 54 ANK proteins are present in P. patens. Based on their differential domain composition, the identified ANK proteins were classified into nine subfamilies. Comparative analysis of the different subfamilies of ANK proteins revealed that P. patens contains almost all the known subgroups of ANK proteins found in the other angiosperm species except for the ones having the TPR domain. Phylogenetic analysis using full length protein sequences supported the subfamily classification where the members of the same subfamily almost always clustered together. Synonymous divergence (dS) and nonsynonymous divergence (dN) ratios showed positive selection for the ANK genes of P. patens which probably helped them to attain significant functional diversity during the course of evolution. Taken together, the data provided here can provide useful insights for future functional studies of the proteins from this superfamily as well as comparative studies of ANK proteins.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".