MHC-NP: Predicting peptides naturally processed by the MHC

被引：41

作者：

Giguere, Sebastien ^{[1
]}

Drouin, Alexandre ^{[1
]}

Lacoste, Alexandre ^{[1
]}

Marchand, Mario ^{[1
]}

Corbeil, Jacques ^{[2
]}

Laviolette, Francois ^{[1
]}

机构：

[1] Univ Laval, Dept Comp Sci & Software Engn, Quebec City, PQ G1V 0A6, Canada

[2] Univ Laval, Dept Mol Med, Quebec City, PQ G1V 0A6, Canada

来源：

JOURNAL OF IMMUNOLOGICAL METHODS | 2013年 / 400卷

基金：

加拿大创新基金会; 加拿大自然科学与工程研究理事会;

关键词：

Machine learning; Kernel; Immunology; Epitope; Vaccinology; MHC; KERNEL;

D O I：

10.1016/j.jim.2013.10.003

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

We present MHC-NP, a tool for predicting peptides naturally processed by the MHC pathway. The method was part of the 2nd Machine Learning Competition in Immunology and yielded state-of-the-art accuracy for the prediction of peptides eluted from human HLA-A*02:01, HLA-B*07:02, HLA-B*35:01, HLA-B*44:03, HIA-B*53:01, HLA-B*57:01 and mouse H2-D-b and H2-K-b MHC molecules. We briefly explain the theory and motivations that have led to developing this tool. General applicability in the field of immunology and specifically epitope-based vaccine are expected. Our tool is freely available online and hosted by the Immune Epitope Database at http://tools.immuneepitope.org/mhcnp/. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：30 / 36

页数：7

共 19 条

[1] The use of the area under the roc curve in the evaluation of machine learning algorithms [J].

Bradley, AP .

PATTERN RECOGNITION, 1997, 30 (07) :1145-1159

[2] SUPPORT-VECTOR NETWORKS [J].

CORTES, C ;

VAPNIK, V .

MACHINE LEARNING, 1995, 20 (03) :273-297

[3]

Elkan C., 2008, PROC 14 ACM SIGKDD I, P213, DOI DOI 10.1145/1401890.1401920

[4] Learning a peptide-protein binding affinity predictor with kernel ridge regression [J].

Giguere, Sebastien ;

Marchand, Mario ;

Laviolette, Francois ;

Drouin, Alexandre ;

Corbeil, Jacques .

BMC BIOINFORMATICS, 2013, 14

[5]

Hastie T., 2009, ELEMENTS STAT LEARNI, DOI DOI 10.1007/978-0-387-84858-7

[6]

Jiang J., 2008, A literature survey on domain adaptation of statistical classifiers

[7]

Joachims T, 1999, MACHINE LEARNING, PROCEEDINGS, P200

[8]

Leslie C., 2002, P PSB, V7, P566

[9] NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11 [J].

Lundegaard, Claus ;

Lamberth, Kasper ;

Harndahl, Mikkel ;

Buus, Soren ;

Lund, Ole ;

Nielsen, Morten .

NUCLEIC ACIDS RESEARCH, 2008, 36 :W509-W512

[10] Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites [J].

Meinicke, P ;

Tech, M ;

Morgenstern, B ;

Merkl, R .

BMC BIOINFORMATICS, 2004, 5 (1)

← 1 2 →