JenPep:  A Novel Computational Information Resource for Immunobiology and Vaccinology

McSparron, Helen; Blythe, Martin; Zygouri, Christianna; Doytchinova, Irini; Flower, Darren R.

doi:10.1021/ci030461e

Cited by 74 publications

(40 citation statements)

References 65 publications

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“…Many prediction methods and databases follow this principal. In contrast to these databases, AntiJen (formerly JenPep) has been developed [26,27], to be the first functional database in immunology to contain quantitative binding data. Unlike other databases (Box 3), this system archives experimental conditions in detail, enabling decisions to be reached regarding the veracity or otherwise of particular data.…”

Section: Glossarymentioning

confidence: 99%

Towards in silico prediction of immunogenic epitopes

Flower

2003

Trends in Immunology

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104

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Section: Glossarymentioning

confidence: 99%

Towards in silico prediction of immunogenic epitopes

Flower

2003

Trends in Immunology

Self Cite

104

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“…The training data containing binding and nonbinding peptides were extracted from SYFPEITHI [16], MHCPEP [30], MHCBN [31], JenPep [32] and a set of known non-binders (V. Brusic, unpublished data). The 9-mer peptides were used for deriving the K d matrix because the majority of peptides that bind K d are 9 amino acid long [33].…”

Section: K D Datasetsmentioning

confidence: 99%

PRED^NOD, a prediction server for peptide binding to the H-2^g7haplotype of the non-obese diabetic mouse

Rajapakse

Zhang

Srinivasan³

et al. 2006

Autoimmunity

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The non-obese diabetic (NOD) mouse is a widely used animal model for study of autoimmune diseases, in particular human type 1 diabetes mellitus (T1DM). Identification of the subset of peptides that bind MHC molecules comprising the H-2g7 haplotype of NOD mouse and thereby representing potential NOD T-cell epitopes is important for research into the pathogenesis and immunotherapy of T1DM. The H-2g7 haplotype comprises the MHC class-I molecules Kd and Db and a single class-II molecule I-Ag7. We have developed a prediction system, PREDNOD, for accurate identification of peptides that bind the MHC molecules constituting the H-2g7 haplotype. PREDNOD is accessible at http://antigen.i2r.a-star.edu.sg/Ag7.

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“…The authors used data collected in JenPep database [108] that contains experimental quantitative data on the MHC-peptide binding. The suggested approach showed the best results compared to four other methods revealing 24 from 25 known T-cell epitopes specified to MHC-II at the benchmark.…”

Section: T Epitope Predictionmentioning

confidence: 99%

“…Identification of TAP-binding peptides is performed with the help of ANN technique [115]. TAP-binding peptides can also be predicted at the JenPep server [108].…”

Section: T Epitope Predictionmentioning

confidence: 99%

Computer Design of Vaccines: Approaches, Software Tools and Informational Resources

Sobolev¹,

Olenina²,

Колесанова³

et al. 2005

CAD

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Development of computer methods in molecular biology and fast growth of microbial genomics data enabled new approach based on selecting in silico antigenic components to design vaccine constructs. It is expected that application of this technology will eliminate side effects of new vaccines and reduce the time consumption and financial expenses. The bioinformatics methods of sequence analysis are used to reveal the most prospective proteins or protein fragments of infectious agents as candidates for vaccine design. In these studies the specialized molecular immunology databases are widely used. The new approach ("Reverse vaccinology") could help in designing vaccines against diseases where traditional methods are not successful, e.g. when the viral genome reveals the extreme variability and permanent changes of antigenic properties that make difficulties for selection of molecular targets for medicines and candidate vaccines. A number of informational resources are already designed to collect and provide genomic data on certain microbes or viruses. The peculiarity of such resources is presentation of data, characterizing the different genomic variants of the same infectious agents. These structural data coupled with information on functional/immune features and software tools have to compose basis for constructing a new generation of vaccines against "common" and new infections such as AIDS, Hepatitis C, and SARS. The approaches published in literature, as well as the authors' original results are discussed.

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JenPep: A Novel Computational Information Resource for Immunobiology and Vaccinology

Cited by 74 publications

References 65 publications

Towards in silico prediction of immunogenic epitopes

Towards in silico prediction of immunogenic epitopes

PRED^NOD, a prediction server for peptide binding to the H-2^g7haplotype of the non-obese diabetic mouse

Computer Design of Vaccines: Approaches, Software Tools and Informational Resources

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JenPep: A Novel Computational Information Resource for Immunobiology and Vaccinology

Cited by 74 publications

References 65 publications

Towards in silico prediction of immunogenic epitopes

Towards in silico prediction of immunogenic epitopes

PREDNOD, a prediction server for peptide binding to the H-2g7haplotype of the non-obese diabetic mouse

Computer Design of Vaccines: Approaches, Software Tools and Informational Resources

Contact Info

Product

Resources

About

PRED^NOD, a prediction server for peptide binding to the H-2^g7haplotype of the non-obese diabetic mouse