Examining Protein Structure and Similarities by Spectral Analysis Technique
Bibliographic record
Abstract
The spectral envelope, a frequency based technique for analyzing categorical time series, is applied to amino acid sequences to examine their periodicity. The periodic signatures of such sequences is related to the secondary structure of the folding patterns in the gene. For a pair of sequences, we define a spectral envelope covariance which emphasizes the common periodicities in the two sequences. This is used to give a similarity measure for the two sequences which can then be used in a neighbour joining algorithm to construct a phylogeny. We apply the spectral methods to myoglobin sequences from primates and cetaceans. The spectral envelope reflects the structure of this protein and the tree constructed using spectral methods shows strong agreement with published trees. The spectral envelope can be used to explore similarities between and within different protein families. Since we do not require aligned sequences, the spectral methods can be used to create phylogenies across different protein families. We apply the method to 11 protein families from PANDIT obtaining a tree where the families are separated and the relationship among the families is given.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".