Abstract
Originalsprog | Engelsk |
---|---|
Tidsskrift | BMC Bioinformatics |
Vol/bind | 8 |
Sider (fra-til) | 424 |
DOI | |
Status | Udgivet - 2007 |
Bibliografisk note
Keywords: Algorithms; Binding Sites; Epitope Mapping; Epitopes, T-Lymphocyte; Protein Binding; Sequence Analysis, Protein; T-Lymphocytes, CytotoxicAdgang til dokumentet
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Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction. / Larsen, Mette V; Lundegaard, Claus; Lamberth, Kasper; Buus, Søren; Lund, Ole; Nielsen, Morten.
I: BMC Bioinformatics, Bind 8, 2007, s. 424.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
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TY - JOUR
T1 - Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction
AU - Larsen, Mette V
AU - Lundegaard, Claus
AU - Lamberth, Kasper
AU - Buus, Søren
AU - Lund, Ole
AU - Nielsen, Morten
N1 - Keywords: Algorithms; Binding Sites; Epitope Mapping; Epitopes, T-Lymphocyte; Protein Binding; Sequence Analysis, Protein; T-Lymphocytes, Cytotoxic
PY - 2007
Y1 - 2007
N2 - BACKGROUND: Reliable predictions of Cytotoxic T lymphocyte (CTL) epitopes are essential for rational vaccine design. Most importantly, they can minimize the experimental effort needed to identify epitopes. NetCTL is a web-based tool designed for predicting human CTL epitopes in any given protein. It does so by integrating predictions of proteasomal cleavage, TAP transport efficiency, and MHC class I affinity. At least four other methods have been developed recently that likewise attempt to predict CTL epitopes: EpiJen, MAPPP, MHC-pathway, and WAPP. In order to compare the performance of prediction methods, objective benchmarks and standardized performance measures are needed. Here, we develop such large-scale benchmark and corresponding performance measures and report the performance of an updated version 1.2 of NetCTL in comparison with the four other methods. RESULTS: We define a number of performance measures that can handle the different types of output data from the five methods. We use two evaluation datasets consisting of known HIV CTL epitopes and their source proteins. The source proteins are split into all possible 9 mers and except for annotated epitopes; all other 9 mers are considered non-epitopes. In the RANK measure, we compare two methods at a time and count how often each of the methods rank the epitope highest. In another measure, we find the specificity of the methods at three predefined sensitivity values. Lastly, for each method, we calculate the percentage of known epitopes that rank within the 5% peptides with the highest predicted score. CONCLUSION: NetCTL-1.2 is demonstrated to have a higher predictive performance than EpiJen, MAPPP, MHC-pathway, and WAPP on all performance measures. The higher performance of NetCTL-1.2 as compared to EpiJen and MHC-pathway is, however, not statistically significant on all measures. In the large-scale benchmark calculation consisting of 216 known HIV epitopes covering all 12 recognized HLA supertypes, the NetCTL-1.2 method was shown to have a sensitivity among the 5% top-scoring peptides above 0.72. On this dataset, the best of the other methods achieved a sensitivity of 0.64. The NetCTL-1.2 method is available at http://www.cbs.dtu.dk/services/NetCTL.All used datasets are available at http://www.cbs.dtu.dk/suppl/immunology/CTL-1.2.php.
AB - BACKGROUND: Reliable predictions of Cytotoxic T lymphocyte (CTL) epitopes are essential for rational vaccine design. Most importantly, they can minimize the experimental effort needed to identify epitopes. NetCTL is a web-based tool designed for predicting human CTL epitopes in any given protein. It does so by integrating predictions of proteasomal cleavage, TAP transport efficiency, and MHC class I affinity. At least four other methods have been developed recently that likewise attempt to predict CTL epitopes: EpiJen, MAPPP, MHC-pathway, and WAPP. In order to compare the performance of prediction methods, objective benchmarks and standardized performance measures are needed. Here, we develop such large-scale benchmark and corresponding performance measures and report the performance of an updated version 1.2 of NetCTL in comparison with the four other methods. RESULTS: We define a number of performance measures that can handle the different types of output data from the five methods. We use two evaluation datasets consisting of known HIV CTL epitopes and their source proteins. The source proteins are split into all possible 9 mers and except for annotated epitopes; all other 9 mers are considered non-epitopes. In the RANK measure, we compare two methods at a time and count how often each of the methods rank the epitope highest. In another measure, we find the specificity of the methods at three predefined sensitivity values. Lastly, for each method, we calculate the percentage of known epitopes that rank within the 5% peptides with the highest predicted score. CONCLUSION: NetCTL-1.2 is demonstrated to have a higher predictive performance than EpiJen, MAPPP, MHC-pathway, and WAPP on all performance measures. The higher performance of NetCTL-1.2 as compared to EpiJen and MHC-pathway is, however, not statistically significant on all measures. In the large-scale benchmark calculation consisting of 216 known HIV epitopes covering all 12 recognized HLA supertypes, the NetCTL-1.2 method was shown to have a sensitivity among the 5% top-scoring peptides above 0.72. On this dataset, the best of the other methods achieved a sensitivity of 0.64. The NetCTL-1.2 method is available at http://www.cbs.dtu.dk/services/NetCTL.All used datasets are available at http://www.cbs.dtu.dk/suppl/immunology/CTL-1.2.php.
U2 - 10.1186/1471-2105-8-424
DO - 10.1186/1471-2105-8-424
M3 - Journal article
C2 - 17973982
VL - 8
SP - 424
JO - Computer Applications in the Biosciences
JF - Computer Applications in the Biosciences
SN - 1471-2105
ER -