[HTML][HTML] Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models

W Liu, X Meng, Q Xu, DR Flower, T Li - BMC bioinformatics, 2006 - Springer
Background The binding between peptide epitopes and major histocompatibility complex
proteins (MHCs) is an important event in the cellular immune response. Accurate prediction …

[HTML][HTML] SVRMHC prediction server for MHC-binding peptides

J Wan, W Liu, Q Xu, Y Ren, DR Flower, T Li - BMC bioinformatics, 2006 - Springer
Background The binding between antigenic peptides (epitopes) and the MHC molecule is a
key step in the cellular immune response. Accurate in silico prediction of epitope-MHC …

Examining the independent binding assumption for binding of peptide epitopes to MHC-I molecules

B Peters, W Tong, J Sidney, A Sette, Z Weng - Bioinformatics, 2003 - academic.oup.com
Motivation: Various methods have been proposed to predict the binding affinities of peptides
to Major Histocompatibility Complex class I (MHC-I) molecules based on experimental …

NetMHCcons: a consensus method for the major histocompatibility complex class I predictions

E Karosiene, C Lundegaard, O Lund, M Nielsen - Immunogenetics, 2012 - Springer
A key role in cell-mediated immunity is dedicated to the major histocompatibility complex
(MHC) molecules that bind peptides for presentation on the cell surface. Several in silico …

Automated benchmarking of peptide-MHC class I binding predictions

T Trolle, IG Metushi, JA Greenbaum, Y Kim… - …, 2015 - academic.oup.com
Motivation: Numerous in silico methods predicting peptide binding to major
histocompatibility complex (MHC) class I molecules have been developed over the last …

[HTML][HTML] Predicting Class II MHC-Peptide binding: a kernel based approach using similarity scores

J Salomon, DR Flower - BMC bioinformatics, 2006 - Springer
Background Modelling the interaction between potentially antigenic peptides and Major
Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell …

Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers

C Lundegaard, O Lund, M Nielsen - Bioinformatics, 2008 - academic.oup.com
Several accurate prediction systems have been developed for prediction of class I major
histocompatibility complex (MHC): peptide binding. Most of these are trained on binding …

Hidden Markov model-based prediction of antigenic peptides that interact with MHC class II molecules

H Noguchi, R Kato, T Hanai, Y Matsubara… - Journal of bioscience …, 2002 - Elsevier
Elucidating the interaction between major histocompatibility complex (MHC) molecules and
antigenic peptides is fundamental to better understanding of the processes involved in …

Coupling in silico and in vitro analysis of peptide-MHC binding: a bioinformatic approach enabling prediction of superbinding peptides and anchorless epitopes

IA Doytchinova, VA Walshe, NA Jones… - The Journal of …, 2004 - journals.aai.org
The ability to define and manipulate the interaction of peptides with MHC molecules has
immense immunological utility, with applications in epitope identification, vaccine design …

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

KK Jensen, M Andreatta, P Marcatili, S Buus… - …, 2018 - Wiley Online Library
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 …