NDLI: Introduction to the Peptide Binding Problem of Computational Immunology: New Results

Content Provider	Springer Nature Link
Author	Xiao, Quan Wu Wong, Hau San Guo, Xin Smale, Stephen Shen, Wen Jun
Copyright Year	2013
Abstract	We attempt to establish geometrical methods for amino acid sequences. To measure the similarities of these sequences, a kernel on strings is defined using only the sequence structure and a good amino acid substitution matrix (e.g. BLOSUM62). The kernel is used in learning machines to predict binding affinities of peptides to human leukocyte antigen DR (HLA-DR) molecules. On both fixed allele (Nielsen and Lund in BMC Bioinform. 10:296, 2009) and pan-allele (Nielsen et al. in Immunome Res. 6(1):9, 2010) benchmark databases, our algorithm achieves the state-of-the-art performance. The kernel is also used to define a distance on an HLA-DR allele set based on which a clustering analysis precisely recovers the serotype classifications assigned by WHO (Holdsworth et al. in Tissue Antigens 73(2):95–170, 2009; Marsh et al. in Tissue Antigens 75(4):291–455, 2010). These results suggest that our kernel relates well the sequence structure of both peptides and HLA-DR molecules to their biological functions, and that it offers a simple, powerful and promising methodology to immunology and amino acid sequence studies.
Ending Page	984
Page Count	34
Starting Page	951
File Format	PDF
ISSN	16153375
e-ISSN	16153383
Journal	Foundations of Computational Mathematics
Issue Number	5
Volume Number	14
Language	English
Publisher	Springer US
Publisher Date	2013-09-17
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Learning and adaptive systems Reproducing kernel Hilbert space Biochemistry, molecular biology Economics general HLA DRB allele classification Linear and Multilinear Algebras, Matrix Theory Peptide binding prediction Applications to biology and medical sciences Major histocompatibility complex Numerical Analysis Computer Science String kernel General biostatistics Applications of Mathematics Math Applications in Computer Science
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Analysis Computational Theory and Mathematics Computational Mathematics

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