An automated benchmarking platform for MHC class II binding prediction methods-Reference-Cited by-同舟云学术

An automated benchmarking platform for MHC class II binding prediction methods

Published:2017-12-21 Issue:9 Volume:34 Page:1522-1528
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Andreatta Massimo¹^ORCID,Trolle Thomas²,Yan Zhen³,Greenbaum Jason A³,Peters Bjoern⁴,Nielsen Morten¹⁵^ORCID

Affiliation:

1. Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, San Martín, Buenos Aires, Argentina

2. Evaxion Biotech, Copenhagen N, Denmark

3. Bioinformatics Core Facility, La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA

4. Division of Vaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA

5. Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark

Funder

National Institutes of Health

CONICET

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/34/9/1522/25120874/btx820.pdf

Reference24 articles.

1. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification;Andreatta;Immunogenetics,2015

2. Pathways of antigen processing;Blum;Annu. Rev. Immunol,2013

3. Automated generation and evaluation of specific MHC binding predictive tools: ARB matrix applications;Bui;Immunogenetics,2005

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