A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction
Human leukocyte antigen class I (HLA-I) molecules are encoded by major histocompatibility
complex (MHC) class I loci in humans. The binding and interaction between HLA-I …
complex (MHC) class I loci in humans. The binding and interaction between HLA-I …
HLA-binding properties of tumor neoepitopes in humans
EF Fritsch, M Rajasagi, PA Ott, V Brusic… - Cancer immunology …, 2014 - AACR
Cancer genome sequencing has enabled the rapid identification of the complete repertoire
of coding sequence mutations within a patient's tumor and facilitated their use as …
of coding sequence mutations within a patient's tumor and facilitated their use as …
Immune epitope database analysis resource
Y Kim, J Ponomarenko, Z Zhu, D Tamang… - Nucleic acids …, 2012 - academic.oup.com
The immune epitope database analysis resource (IEDB-AR: http://tools. iedb. org) is a
collection of tools for prediction and analysis of molecular targets of T-and B-cell immune …
collection of tools for prediction and analysis of molecular targets of T-and B-cell immune …
Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes
W Zhao, X Sher - PLoS computational biology, 2018 - journals.plos.org
A number of machine learning-based predictors have been developed for identifying
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …
immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II …
Supramolecular immunotherapy of cancer based on the self‐assembling peptide design
R Chang, X Yan - Small Structures, 2020 - Wiley Online Library
Supramolecular peptide assemblies with specific motifs have the advantages of high
immunogenicity, regulated immune response, and increased multiple functions in improving …
immunogenicity, regulated immune response, and increased multiple functions in improving …
RACER-m leverages structural features for sparse T cell specificity prediction
Reliable prediction of T cell specificity against antigenic signatures is a formidable task,
complicated by the immense diversity of T cell receptor and antigen sequence space and …
complicated by the immense diversity of T cell receptor and antigen sequence space and …
Deep convolutional neural networks for pan-specific peptide-MHC class I binding prediction
Y Han, D Kim - BMC bioinformatics, 2017 - Springer
Background Computational scanning of peptide candidates that bind to a specific major
histocompatibility complex (MHC) can speed up the peptide-based vaccine development …
histocompatibility complex (MHC) can speed up the peptide-based vaccine development …
Removing T-cell epitopes with computational protein design
C King, EN Garza, R Mazor… - Proceedings of the …, 2014 - National Acad Sciences
Immune responses can make protein therapeutics ineffective or even dangerous. We
describe a general computational protein design method for reducing immunogenicity by …
describe a general computational protein design method for reducing immunogenicity by …
Main strategies for the identification of neoantigens
AV Gopanenko, EN Kosobokova, VS Kosorukov - Cancers, 2020 - mdpi.com
Simple Summary This review provides an overview of currently available approaches
applied for neoantigens discovery—tumor-specific peptides that appeared due to the …
applied for neoantigens discovery—tumor-specific peptides that appeared due to the …
Structure-based methods for binding mode and binding affinity prediction for peptide-MHC complexes
Understanding the mechanisms involved in the activation of an immune response is
essential to many fields in human health, including vaccine development and personalized …
essential to many fields in human health, including vaccine development and personalized …