Strategies to Query and Display Allergy-Derived Epitope Data from the Immune Epitope Database
Bibliographic record
Abstract
The recognition of specific epitopes on allergens by antibodies and T cells is a key element in allergic processes. Analysis of epitope data may be of interest for basic immunopathology or for potential application in diagnostics or immunotherapy. The Immune Epitope Database (IEDB) is a freely available repository of epitope data from infectious disease agents, as well as epitopes defined for allergy, autoimmunity, and transplantation. The IEDB curates the experiments associated with each epitope and thus provides a variety of different ways to search the data. This review aims to demonstrate the utility of the IEDB and its query strategies, including searching by epitope structure (peptidic/nonpeptidic), by assay methodology, by host, by the allergen itself, or by the organism from which the allergen was derived. Links to tools for visualization of 3-D structures, epitope prediction, and analyses of B and T cell reactivity by host response frequency score are also highlighted.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".