Evidence map›Paper›PMID 29315598›Full record

ArticleImmunology2018

Improved methods for predicting peptide binding affinity to MHC class II molecules.

Kamilla Kjaergaard Jensen, Massimo Andreatta, Paolo Marcatili, Søren Buus, Jason A Greenbaum, Zhen Yan, Alessandro Sette, Bjoern Peters, Morten Nielsen

Open access · bronzeAbstract read
In one paragraph

Article in Immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 471 papers.

0numbers the graph read from it
0cells of the map it votes in
471citing papers in PubMed
33.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

471 citing papers in PubMed, 799 citations in OpenAlex.

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  17. Molecular origin, discovery, validation and application of neoantigens.Asian journal of pharmaceutical sciences · 2026
    Review
  18. Article
  19. Article
  20. HLA-DQB1*03:01 and risk of HBV-related HCC.Hepatology (Baltimore, Md.) · 2026
    Article

411 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 3 countries.

Kamilla Kjaergaard JensenDepartment of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark.ORCID 0000-0001-9217-7142
Massimo AndreattaInstituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, Buenos Aires, Argentina.ORCID 0000-0002-8036-2647
Paolo MarcatiliDepartment of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark.
Søren BuusDepartment of Immunology and Microbiology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
Jason A GreenbaumBioinformatics Core Facility, La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA.
Zhen YanBioinformatics Core Facility, La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA.
Alessandro SetteDivision of Vaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA.
Bjoern PetersDivision of Vaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA.
Morten NielsenDepartment of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark.ORCID 0000-0001-7885-4311
La Jolla Institute for Immunology · USNational University of General San Martín · ARTechnical University of Denmark · DKUniversity of Copenhagen · DK

Funding

NIAID NIH HHS HHSN272201200010C
6 · The paper itself

Abstract

Major histocompatibility complex class II (MHC-II) molecules are expressed on the surface of professional antigen-presenting cells where they display peptides to T helper cells, which orchestrate the onset and outcome of many host immune responses. Understanding which peptides will be presented by the MHC-II molecule is therefore important for understanding the activation of T helper cells and can be used to identify T-cell epitopes. We here present updated versions of two MHC-II-peptide binding affinity prediction methods, NetMHCII and NetMHCIIpan. These were constructed using an extended data set of quantitative MHC-peptide binding affinity data obtained from the Immune Epitope Database covering HLA-DR, HLA-DQ, HLA-DP and H-2 mouse molecules. We show that training with this extended data set improved the performance for peptide binding predictions for both methods. Both methods are publicly available at www.cbs.dtu.dk/services/NetMHCII-2.3 and www.cbs.dtu.dk/services/NetMHCIIpan-3.2.

Indexed as

Amino Acid SequenceComputational BiologyDatabases, ProteinEpitope MappingEpitopesEpitopes, T-LymphocyteHistocompatibility Antigens Class IIHumansOligopeptidesProtein BindingReproducibility of ResultsEpitopesEpitopes, T-LymphocyteHistocompatibility Antigens Class IIMHC binding peptideOligopeptidesaffinity predictionsimmunogenic peptidesMHC binding specificitypeptide-MHC bindingT-cell epitope

Identifiers

PMID29315598
PMCPMC6002223
OpenAlexW2783102765

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.