Evidence map›Paper›PMID 23229472›Full record

ArticleImmunogenetics2013

Consensus classification of human leukocyte antigen class II proteins.

Indrajit Saha, Giovanni Mazzocco, Dariusz Plewczynski

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Immunogenetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

3 citing papers in PubMed, 16 citations in OpenAlex.

  1. Computational Methods for Cancer Neoantigen Prediction.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  2. Article
  3. Classification of human leukocyte antigen (HLA) supertypes.Methods in molecular biology (Clifton, N.J.) · 2014
    Article
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Indrajit SahaInterdisciplinary Centre for Mathematical and Computational Modeling, University of Warsaw, Warsaw, Poland.
Giovanni Mazzocco
Dariusz Plewczynski
University of Warsaw · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Class II human leukocyte antigens (HLA II) are proteins involved in the human immunological adaptive response by binding and exposing some pre-processed, non-self peptides in the extracellular domain in order to make them recognizable by the CD4+ T lymphocytes. However, the understanding of HLA-peptide binding interaction is a crucial step for designing a peptide-based vaccine because the high rate of polymorphisms in HLA class II molecules creates a big challenge, even though the HLA II proteins can be grouped into supertypes, where members of different class bind a similar pool of peptides. Hence, first we performed the supertype classification of 27 HLA II proteins using their binding affinities and structural-based linear motifs to create a stable group of supertypes. For this purpose, a well-known clustering method was used, and then, a consensus was built to find the stable groups and to show the functional and structural correlation of HLA II proteins. Thus, the overlap of the binding events was measured, confirming a large promiscuity within the HLA II-peptide interactions. Moreover, a very low rate of locus-specific binding events was observed for the HLA-DP genetic locus, suggesting a different binding selectivity of these proteins with respect to HLA-DR and HLA-DQ proteins. Secondly, a predictor based on a support vector machine (SVM) classifier was designed to recognize HLA II-binding peptides. The efficiency of prediction was estimated using precision, recall (sensitivity), specificity, accuracy, F-measure, and area under the ROC curve values of random subsampled dataset in comparison with other supervised classifiers. Also the leave-one-out cross-validation was performed to establish the efficiency of the predictor. The availability of HLA II-peptide interaction dataset, HLA II-binding motifs, high-quality amino acid indices, peptide dataset for SVM training, and MATLAB code of the predictor is available at http://sysbio.icm.edu.pl/HLA .

Indexed as

AlgorithmsBinding SitesCluster AnalysisComputational BiologyHistocompatibility Antigens Class IIHumansPeptidesPhylogenyProtein BindingReproducibility of ResultsHistocompatibility Antigens Class IIPeptides

Identifiers

PMID23229472
PMCPMC3543608
OpenAlexW2061367389

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.