Title
Netmhc-3.0: Accurate Web Accessible Predictions Of Human, Mouse And Monkey Mhc Class I Affinities For Peptides Of Length 8-11
Abstract
NetMHC-3.0 is trained on a large number of quantitative peptide data using both affinity data from the Immune Epitope Database and Analysis Resource (IEDB) and elution data from SYFPEITHI. The method generates high-accuracy predictions of major histocompatibility complex (MHC): peptide binding. The predictions are based on artificial neural networks trained on data from 55 MHC alleles (43 Human and 12 non-human), and position-specific scoring matrices (PSSMs) for additional 67 HLA alleles. As only the MHC class I prediction server is available, predictions are possible for peptides of length 811 for all 122 alleles. artificial neural network predictions are given as actual IC50 values whereas PSSM predictions are given as a log-odds likelihood scores. The output is optionally available as download for easy post-processing. The training method underlying the server is the best available, and has been used to predict possible MHC-binding peptides in a series of pathogen viral proteomes including SARS, Influenza and HIV, resulting in an average of 7580 confirmed MHC binders. Here, the performance is further validated and benchmarked using a large set of newly published affinity data, non-redundant to the training set. The server is free of use and available at: http://www.cbs.dtu.dk/services/NetMHC.
Year
DOI
Venue
2008
10.1093/nar/gkn202
NUCLEIC ACIDS RESEARCH
Keywords
Field
DocType
epitopes,web accessibility,mhc class i,alleles,internet,hla antigens
Epitope,Immune Epitope Database and Analysis Resource,Biology,MHC class I,Proteome,Major histocompatibility complex,Human leukocyte antigen,Artificial neural network,Genetics,Affinities
Journal
Volume
Issue
ISSN
36
Web Server issue
0305-1048
Citations 
PageRank 
References 
21
1.41
4
Authors
6
Name
Order
Citations
PageRank
Claus Lundegaard136527.39
Kasper Lamberth218313.05
Mikkel Harndahl3826.73
S Buus418013.44
Ole Lund552744.47
Morten Nielsen646931.89