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OptiTope
Aims at assisting immunologists in designing epitope-based vaccines. OptiTope maximizes overall immunogenicity with respect to the user's requirements. The overall immunogenicity of an epitope set depends on the immunogenicity of its components with respect to the MHC alleles in the target population. Furthermore, the contribution of an MHC allele directly depends on its probability of occuring within the target population. More common alleles are weighted more than uncommon ones. Thus, the overall immunogenicity of a set of epitopes can be derived as the sum of the components' immunogenicities weighted by the probability of the respective MHC allele. With OptiTope, we provide an easy-to-use tool to determine a provably optimal set of epitopes with respect to overall immunogenicity in a specific individual (personalized medicine) or a target population (e.g. a certain ethnic group).
PEPVAC / Promiscuous EPitope-based VACcine
Allows prediction of promiscuous epitopes to five human leukocyte antigen (HLA) I. PEPVAC combines predictions of supertypic peptide binders with the prediction of proteasomal cleavage using probabilistic language models. This tool offers an easy to use interface where sections are divided as follow: input and limitations; supertypes and thresholds; proteasome cleavage. It displays a summary of predictions, including the chosen selections, the number of predicted peptides and the minimum population coverage provided by the supertypic selection.
Mosaic Vaccine Tool Suite
A suite of on-line tools to design candidate vaccine proteins, and to assess antigen potential, using coverage of k-mers (as proxies for potential T-cell epitopes) as a metric. The vaccine design tool uses the recently published 'mosaic' method to generate protein sequences optimized for coverage of high-frequency k-mers; the coverage-assessment tools facilitate coverage comparisons for any potential antigens. These tools simplify generation and quantitative evaluation of prospective antigens, and could be applied to any variable pathogen.
Hotspot Hunter
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A web-based computational system for large-scale screening and selection of candidate immunological hotspots in pathogen proteomes through analysis of antigenic diversity. Hotspot Hunter allows screening and selection of hotspots specific to four common HLA supertypes, namely HLA class I A2, A3, B7 and class II DR. The system uses artificial neural network and support vector machine methods as predictive engines. Soft computing principles were employed to integrate the prediction results produced by both methods for robust prediction performance. Experimental validation of the predictions showed that hotspot hunter can successfully identify majority of the real hotspots.
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