Protein Visualizer 2.0: Intuitive and Interactive Visualization of Protein Topology and Co/Post-Translational Modifications
Bibliographic record
Abstract
Topology and post-translational modifications (PTMs) are critical features in studying the structures and functions of proteins. Several popular and detailed protein visualization algorithms are available for such studies, such as PyMOL, NCBI's iCn3D, UniProt PTM viewing, and Protter. However, none of the studies depict the special relationships between key structural features such as N-glycosylation, disulfide bonds, potential N-glycosylation sites (free sequons), potential disulfide bonds (free cysteine sites), and protein topology in a way conducive to detailed analyses. We introduce Protein Visualizer 2.0 (https://sfu-sun-lab.github.io/protein-visualizer-2.0/), a web-based tool that visualizes these features and the topology of all human proteins. This tool allows users to readily assess potential conflicts among predicted protein topology and known co/post-translational modifications. This tool also helps to reveal hidden relationships among displayed structural features.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".