High-order neural networks and kernel methods for peptide-MHC binding prediction

Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions

(2014) Yohan Kim et al.   BMC BIOINFORMATICS

Learning a peptide-protein binding affinity predictor with kernel ridge regression

(2013) Sébastien Giguère et al.   BMC BIOINFORMATICS

Modeling Natural Images Using Gated MRFs

(2013) Marc'Aurelio Ranzato et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

MHC-NP: Predicting peptides naturally processed by the MHC

(2013) Sébastien Giguère et al.   JOURNAL OF IMMUNOLOGICAL METHODS

POPISK: T-cell reactivity prediction using support vector machines and string kernels

(2011) Chun-Wei Tung et al.   BMC BIOINFORMATICS

Prediction of epitopes using neural network based methods

(2010) Claus Lundegaard et al.   JOURNAL OF IMMUNOLOGICAL METHODS

The Immune Epitope Database 2.0

(2009) Randi Vita et al.   NUCLEIC ACIDS RESEARCH

Learning to represent visual input

(2009) G. E. Hinton   PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES

Pan-specific MHC class I predictors: a benchmark of HLA class I pan-specific prediction methods

(2008) Hao Zhang et al.   BIOINFORMATICS

NetMHCpan, a method for MHC class I binding prediction beyond humans

(2008) Ilka Hoof et al.   IMMUNOGENETICS