Back to results
Bibliographic record · Consultation and access
Artículo

Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction

Wendorff, Mareike et al · Frontiers Media · 2020

Open-access full text
Quick overview. Review the resource’s basic details, then access the content using the main button. This page shows only the information needed to identify, cite, and open the work.
Serial publication

A Chlamydia trachomatis CPAF-STING agonist conjugate vaccine administered intramuscularly and intradermally is immunogenic in the pig model

This serial publication contains 143 related contents.

Resource access

Open the content from the main option or choose another available source.

CONICET Digital CONICET Digital OAI-PMH
Entrar por CONICET Digital
Main access

Open-access full text

Texto completo identificado como acceso abierto.
Open text

Summary

Descripción general del contenido del recurso.

Human Leukocyte Antigen class II (HLA-II) molecules present peptides to T lymphocytes and play an important role in adaptive immune responses. Characterizing the binding specificity of single HLA-II molecules has profound impacts for understanding cellular immunity, identifying the cause of autoimmune diseases, for immunotherapeutics, and vaccine development. Here, novel high-density peptide microarray technology combined with machine learning techniques were used to address this task at an unprecedented level of high-throughput. Microarrays with over 200,000 defined peptides were assayed with four exemplary HLA-II molecules. Machine learning was applied to mine the signals. The comparison of identified binding motifs, and power for predicting eluted ligands and CD4+ epitope datasets to that obtained using NetMHCIIpan-3.2, confirmed a high quality of the chip readout. These results suggest that the proposed microarray technology offers a novel and unique platform for large-scale unbiased interrogation of peptide binding preferences of HLA-II molecules. Fil: Wendorff, Mareike. Christian Albrechts Universitat Zu Kiel.; Alemania Fil: García Álvarez, Heli Magalí. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; Argentina

How to cite

Elegí el formato que necesitás y copiá la referencia al portapapeles.

APA 7

Wendorff, M. E. A. (2020). Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction. http://hdl.handle.net/11336/267498

MLA

Wendorff, Mareike et al. "Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction." 2020. http://hdl.handle.net/11336/267498.

Chicago

Wendorff, Mareike et al. 2020. "Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction.". http://hdl.handle.net/11336/267498.

Harvard

Wendorff, M. E. A. 2020, Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction, Frontiers Media, available at: http://hdl.handle.net/11336/267498 [Accessed 7 Aug. 2026].

Share and print

Save the record, copy its permanent link, or print it as a PDF.

Export reference

You can export the record in common formats for use in a reference manager.

Resource details

Bibliographic information to help confirm that this is the correct material.

Title
Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction
Author / contributors
Wendorff, Mareike et al
Publisher
Frontiers Media
Publication year
2020
ISSN
1664-3224
ISSN
1664-3224
Language
English

Subjects

Explore related resources through these subjects.

Copied