PhosphoSitePlus: a comprehensive resource for investigating the structure and function of experimentally determined post-translational modifications in man and mouse
Bibliographic record
Abstract
PhosphoSitePlus (http://www.phosphosite.org) is an open, comprehensive, manually curated and interactive resource for studying experimentally observed post-translational modifications, primarily of human and mouse proteins. It encompasses 1,30,000 non-redundant modification sites, primarily phosphorylation, ubiquitinylation and acetylation. The interface is designed for clarity and ease of navigation. From the home page, users can launch simple or complex searches and browse high-throughput data sets by disease, tissue or cell line. Searches can be restricted by specific treatments, protein types, domains, cellular components, disease, cell types, cell lines, tissue and sequences or motifs. A few clicks of the mouse will take users to substrate pages or protein pages with sites, sequences, domain diagrams and molecular visualization of side-chains known to be modified; to site pages with information about how the modified site relates to the functions of specific proteins and cellular processes and to curated information pages summarizing the details from one record. PyMOL and Chimera scripts that colorize reactive groups on residues that are modified can be downloaded. Features designed to facilitate proteomic analyses include downloads of modification sites, kinase-substrate data sets, sequence logo generators, a Cytoscape plugin and BioPAX download to enable pathway visualization of the kinase-substrate interactions in PhosphoSitePlus®.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.076 | 0.057 |
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".