Using Gaussian process with test rejection to detect T-cell epitopes in pathogen genomes

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 7, Issue 4, 2010, Pages 741-751

  You, Liwen ^a   Brusic, Vladimir ^b   Gallagher, Marcus ^c   Bodén, Mikael ^c  

^a LUND UNIVERSITY   (Sweden)

^b DANA FARBER CANCER INSTITUTE   (United States)

^c UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

amino acid sequence; epitope; False positive; false positives.; Gaussian processes; Immunology; machine learning; Machine learning; regression; Regression

Indexed keywords

AMINO ACID SEQUENCE; EPITOPE; FALSE POSITIVE; GAUSSIAN PROCESSES; MACHINE-LEARNING; REGRESSION;

AMINO ACIDS; FORECASTING; GAUSSIAN NOISE (ELECTRONIC); GENES; IMMUNOLOGY; LEARNING SYSTEMS; PATHOGENS; PEPTIDES; POLYPEPTIDES; REACTOR CORES; REGRESSION ANALYSIS; TESTING; UNCERTAINTY ANALYSIS; VIRUSES;

GAUSSIAN DISTRIBUTION;

VACCINIA VIRUS;

EPITOPE;

ALGORITHM; ARTICLE; EPITOPE MAPPING; GENETICS; IMMUNOLOGY; NORMAL DISTRIBUTION; PATHOGENICITY; VACCINIA VIRUS; VIRUS GENOME;

ALGORITHMS; EPITOPE MAPPING; EPITOPES, T-LYMPHOCYTE; GENOME, VIRAL; NORMAL DISTRIBUTION; VACCINIA VIRUS;

EID: 78149281499     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2008.131     Document Type: Article

References (23)

1. J.W. Yewdell and J.R. Bennink, "Immunodominance in Major Histocompatibility Complex Class I-Restricted T Lymphocyte Responses," Ann. Rev. Immunology, vol. 17, pp. 51-88, 1999.
2. N. Zaitlen, M. Reyes-Gomez, D. Heckerman, and N. Jojic, "Shift-Invariant Adaptive Double Threading: Learning MHC II - Peptide Binding," Lecture Notes in Computer Science, Springer, 2007.
3. P.A. Reche, J.-P. Gluttinga, and E.L. Reinherz, "Prediction of MHC Class I Binding Peptides Using Profile Motifs," Human Immunology, vol. 63, pp. 701-709, 2002.
4. H.H. Bui, J. Sidney, B. Peters, M. Sathiamurthy, A. Sinichi, K.A. Purton, B.R. Mothe, F.V. Chisari, D.I. Watkins, and A. Sette, "Automated Generation and Evaluation of Specific MHC Binding Predictive Tools: ARB Matrix Applications," Immunogenetics, vol. 57, pp. 304-314, 2005.
5. B. Peters, W. Tong, J. Sidney, A. Sette, and Z. Weng, "Examining the Independent Binding Assumption for Binding of Peptide Epitopes to MHC I Molecules," Bioinformatics, vol. 19, pp. 1765-1772, 2003.
6. B. Peters and A. Sette, "Generating Quantitative Models Describing the Sequence Specificity of Biological Processes with the Stabilized Matrix Method," BMC Bioinformatics, vol. 6, article no. 132, May 2005.
7. K. Udaka, K.H. Wiesmuller, S. Kienle, G. Jung, H. Tamamura, H. Yamagishi, K. Okumura, P. Walden, T. Suto, and T. Kawasaki, "An Automated Prediction of MHC Class I-Binding Peptides Based on Positional Scanning with Peptide Libraries," Immunogenetics, vol. 51, pp. 816-828, 2000.
8. K.C. Parker, M.A. Bednarek, and J.E. Coligan, "Scheme for Ranking Potential HLA-A2 Binding Peptides Based on Independent Binding of Individual Peptide Side Chains," J. Immunology, vol. 152, pp. 163-175, 1994.
9. M.C. Honeyman, V. Brusic, N.L. Stone, and L.C. Harrison, "Neural Network-Based Prediction of Candidate T-Cell Epitopes," Nature Biotechnology, vol. 16, no. 10, pp. 966-969, Oct. 1998.
10. M. Nielsen, C. Lundegaard, P. Worning, S.L. Lauemoller, K. Lamberth, S. Buus, S. Brunak, and O. Lund, "Reliable Prediction of T-Cell Epitopes Using Neural Networks with Novel Sequence Representations," Protein Science, vol. 12, pp. 1007-1017, 2003.
11. P. Dönnes and A. Elofsson, "Prediction of MHC Class I Binding Peptides, Using SVMHC," BMC Bioinformatics, vol. 3, article no. 25, Sept. 2002.
12. Y. Zhao, C. Pinilla, D. Valmori, R. Martin, and R. Simon, "Application of Support Vector Machines for T-Cell Epitopes Prediction," Bioinformatics, vol. 19, pp. 1978-1984, 2003.
13. H. Riedesel, B. Kolbeck, O. Schmetzer, and E.W. Knapp, "Peptide Binding at Class I Major Histocompatibility Complex Scored with Linear Functions and Support Vector Machines," Genome Informatics, vol. 15, pp. 198-212, 2004.
14. G.L. Zhang, I. Bozic, C.K. Kwoh, J.T. August, and V. Brusic, "Prediction of Supertypespecific HLA Class I Binding Peptides Using Support Vector Machines," J. Immunological Methods, vol. 320, pp. 143-154, 2007.
15. H. Mamitsuka, "Predicting Peptides That Bind to MHC Molecules Using Supervised Learning of Hidden Markov Models," Proteins, vol. 33, pp. 460-474, 1998.
16. T. Hertz and C. Yanover, "PepDist: A New Framework for Protein-Peptide Binding Prediction Based on Learning Peptide Distance Functions," BMC Bioinformatics, vol. 7, no. 1, Suppl 1: S3, Mar. 2006.
17. M. Moutaftsi, B. Peters, V. Pasquetto, D.C. Tscharke, J. Sidney, H.H. Bui, H. Grey, and A. Sette, "A Consensus Epitope Prediction Approach Identifies the Breadth of Murine T(CD8+)-Cell Responses to Vaccinia Virus," Nature Biotechnology, vol. 24, pp. 817-819, 2006.
18. D.J.C. MacKay, "Introduction to Gaussian Processes," Neural Networks and Machine Learning, C.M. Bishop, ed., vol. 168, pp. 133-165, Springer-Verlag, 1998.
19. C.E. Rasmussen and C.K.I. Williams, Gaussian Processes for Machine Learning, first ed. The MIT Press, 2006.
20. M. Seeger, "Gaussian Processes for Machine Learning," Int'l J. Neural Systems, vol. 14, pp. 69-106, 2004.
21. B. Peters, H.H. Bui, S. Frankild, M. Nielson, C. Lundegaard, E. Kostem, D. Basch, K. Lamberth, M. Harndahl, W. Fleri, S.S. Wilson, J. Sidney, O. Lund, S. Buus, and A. Sette, "A Community Resource Benchmarking Predictions of Peptide Binding to MHC I Molecules," PLoS Computational Biology, vol. 2, pp. 574-584, 2006.
22. C.C. Chang and C.J. Lin, "LIBSVM: A Library for Support Vector Machines," http://www.csie.ntu.edu.tw/cjlin/libsvm, 2001.
23. P. Rao and M.J. Katzoff, "Bootstrap for Finite Populations," Comm. Statistics - Simulation and Computation, vol. 25, pp. 979-994, 1996.