In silico prediction of peptide-MHC binding affinity using SVRMHC.

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Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models. BMC Bioinformatics (2006) 1.22

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Molecular basis of peptide recognition by the TCR: affinity differences calculated using large scale computing. J Immunol (2005) 0.96

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New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity. Org Biomol Chem (2004) 0.92

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity: in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique. J Chem Inf Model (2006) 0.91

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Peptide binding prediction for the human class II MHC allele HLA-DP2: a molecular docking approach. BMC Struct Biol (2011) 0.91

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A comparative molecular similarity index analysis (CoMSIA) study identifies an HLA-A2 binding supermotif. J Comput Aided Mol Des (2003) 0.90

MHCPred 2.0: an updated quantitative T-cell epitope prediction server. Appl Bioinformatics (2006) 0.90

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Large-scale molecular dynamics simulations of HLA-A*0201 complexed with a tumor-specific antigenic peptide: can the alpha3 and beta2m domains be neglected? J Comput Chem (2004) 0.88

In silico prediction of peptide binding affinity to class I mouse major histocompatibility complexes: a comparative molecular similarity index analysis (CoMSIA) study. J Chem Inf Model (2005) 0.88

Peptide length significantly influences in vitro affinity for MHC class II molecules. Immunome Res (2008) 0.88

Peptide recognition by the T cell receptor: comparison of binding free energies from thermodynamic integration, Poisson-Boltzmann and linear interaction energy approximations. Philos Trans A Math Phys Eng Sci (2005) 0.87

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Homeostatic adaptations in brain energy metabolism in mouse models of Huntington disease. J Cereb Blood Flow Metab (2012) 0.86

Class I T-cell epitope prediction: improvements using a combination of proteasome cleavage, TAP affinity, and MHC binding. Mol Immunol (2006) 0.86

Peptide binding to the HLA-DRB1 supertype: a proteochemometrics analysis. Eur J Med Chem (2009) 0.86

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Optimizing amino acid groupings for GPCR classification. Bioinformatics (2008) 0.84

Toward the atomistic simulation of T cell epitopes automated construction of MHC: peptide structures for free energy calculations. J Mol Graph Model (2007) 0.84

Statistical deconvolution of enthalpic energetic contributions to MHC-peptide binding affinity. BMC Struct Biol (2006) 0.83

Modeling the peptide-T cell receptor interaction by the comparative molecular similarity indices analysis-soft independent modeling of class analogy technique. J Med Chem (2006) 0.83

Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics: comparison of discriminant analysis and multiple linear regression. J Chem Inf Model (2007) 0.83

Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes. PLoS One (2009) 0.83

Feedback regulation of NEUROG2 activity by MTGR1 is required for progression of neurogenesis. Mol Cell Neurosci (2009) 0.83

EpiTOP--a proteochemometric tool for MHC class II binding prediction. Bioinformatics (2010) 0.83

Human-specific microRNA regulation of FOXO1: implications for microRNA recognition element evolution. Hum Mol Genet (2013) 0.82

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Immunoinformatic evaluation of multiple epitope ensembles as vaccine candidates: E coli 536. Bioinformation (2012) 0.82

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Identification of the HLA-DM/HLA-DR interface. Mol Immunol (2007) 0.81

Quantitative structure-activity relationships and the prediction of MHC supermotifs. Methods (2004) 0.80

Qualitative and quantitative analysis of peptide microarray binding experiments using SVM-PEPARRAY. Methods Mol Biol (2009) 0.79