Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 290

The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.

Precise prediction of major histocompatibility complex class II-peptide interaction based on peptide side chain scanning.

Open access
Hammer, J, Bono, E, Gallazzi, F, Belunis, C, Nagy, Z, Sinigaglia, F·1994·The Journal of experimental medicine

Abstract

We describe here a new method for predicting class II major histocompatibility complex-binding peptides, based on the preferences observed in a systematic series of peptide binding experiments where each position in a "minimal" peptide was replaced individually by every amino acid. The DRB1*0401 peptide binding preferences were determined and incorporated into a computer program that looks through sequences for potential epitopes and assigns each a score. These scores correlate well with previously determined T cell epitopes of foreign antigens and endogenous peptides from self proteins. Our findings hold implications for the design of subunit vaccines and in the identification of autoantigenic peptide regions within self proteins.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1084/jem.180.6.2353

Cites

18 of 18 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 18 references

Cited by

See all 290

Metadata

Authors
Hammer, J., Bono, E., Gallazzi, F., Belunis, C., Nagy, Z., & Sinigaglia, F.
Venue
The Journal of experimental medicine
Published
1994-12-01
Volume
180
Issue
6
Pages
2353-2358
ISSN
  • 0022-1007 (ISSN-L)
  • 1540-9538
OpenAlex
W2021002908
Cited by
290
References
18
FWCI
5.76
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Precise prediction of major histocompatibility complex class II-peptide interaction based on peptide side chain scanning. https://app.cochat.ai/papers/10.1084/jem.180.6.2353
The paper
Hammer, J., Bono, E., Gallazzi, F., Belunis, C., Nagy, Z., & Sinigaglia, F. (1994). Precise prediction of major histocompatibility complex class II-peptide interaction based on peptide side chain scanning. The Journal of experimental medicine. https://doi.org/10.1084/jem.180.6.2353

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.