GOmotif: A web server for investigating the biological role of protein sequence motifs
Bibliographic record
Abstract
BACKGROUND: Many proteins contain conserved sequence patterns (motifs) that contribute to their functionality. The process of experimentally identifying and validating novel protein motifs can be difficult, expensive, and time consuming. A means for helping to identify in advance the possible function of a novel motif is important to test hypotheses concerning the biological relevance of these motifs, thus reducing experimental trial-and-error. RESULTS: GOmotif accepts PROSITE and regular expression formatted motifs as input and searches a Gene Ontology annotated protein database using motif search tools. The search returns the set of proteins containing matching motifs and their associated Gene Ontology terms. These results are presented as: 1) a hierarchical, navigable tree separated into the three Gene Ontology biological domains - biological process, cellular component, and molecular function; 2) corresponding pie charts indicating raw and statistically adjusted distributions of the results, and 3) an interactive graphical network view depicting the location of the results in the Gene Ontology. CONCLUSIONS: GOmotif is a web-based tool designed to assist researchers in investigating the biological role of novel protein motifs. GOmotif can be freely accessed at http://www.gomotif.ca.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".