EpiToolKit 2.0

ABI EpiToolKit is a service of the Applied Bioinformatics Group at University of Tuebingen. The aim of this website and its services is to support immunological research. It provides a collection of methods from computational immunology for the development of novel epitope-based vaccines including HLA ligand or potential T-Cell epitope prediction, an epitope selection framework for vaccine design, and a method to design optimal string-of-beads vaccines. Additionally, EpiToolKit provides several other tools ranging from HLA typing based on NGS data, to prediction of polymorphic peptides.

Under Single Tools each tool provides a short description of its current step, and assistance to guide inexperienced users. For more experienced users, the Workflow section provides the capability to combine the different tools to large workflows creating huge variability in the usage of our tools.

Data Management

All uploaded data are private, but can be shared with users if desired.
Data of unregistered users and delete data will be permanently deleted after 7 days.

User Accounts

To create an account, register under User->Register or click here. Alternatively, a guest account is provided with login test_user@informatik.uni-tuebingen.de and password workflowTest. Please note that the guest account shares uploaded data with all other guest users. If you want to keep your data private, use the server without logging in or create your own account.


We are proud to announce a new tool, called Spacer Design, for string-of-beads design with flexible spacers/linkers. It optimally determines the length and spacer sequence, as well as the ordering of the epitopes included in the string-of-beads vaccines.

In addition, we added new epitope (SMM, SMMPMEC) and cleavage site (ProteaSMM) prediction tools.

HLA Genotyping

EpitToolKit provides an interface to OptiType a novel approach for HLA genotyping based on NGS data. OptiType uses integer linear programming to solve a customized formulation of the well known maximum set covering problem. In doing so, OptiType selects simultaneously the most likely HLA allele combination.

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Epitope Prediction

Epitope prediction provides several methods for predicting potential T-Cell epitopes. Different sequence input options provide access to the protein databases like NCBI RefSeq and UniProt. Additionally, own sequences can be entered for prediction. Methods and alleles are available for HLA class I and HLA class II epitope prediction.

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Polymorphic Epitope Prediction

Polymorphic Epitope Prediction is based on SNEP and extends Epitope Prediction by incorporating variant information. From these variants neoantigens are constructed which enables the discovery of neoepitopes that are influenced by the used variant information. These neoepitopes play an important role in cancer immunotherapy since they usually are novel peptide sequences that can only be found the tumor cells. These epitopes therefore represent promising targets for personalized cancer vaccines.

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Epitope Selection

Epitope selection is the most important step for vaccine design. It is concerned with selecting a small set of candidate epitopes to maximize the probability of inducing a long lasting and strong immune response. Epitope Selection is an interface to OptiTope a highly flexible mathematical framework for epitope selection. OptiTope determines the provably optimal epitope set that maximizes the overall immunogenicity for a target population or a single person and user specified requirements.

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Epitope Assembly

Epitope Assembly is concerned with ordering epitopes into a string-of-beads poly-peptide which maximizes the probability that the epitopes will be fully recovered after proteasomal cleavage. This is an important step for vaccine design and has potentially high impact on the efficacy of the designed vaccine. Epitope Assembly formulates the epitope ordering problem as a traveling salesperson problem where epitopes represent the cities to visit and the distances between the cities represent the recovery probabilities.

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Spacer Design

Spacer Design determines string-of-beads vaccines in optimal order and with connecting spacer sequences of flexible length such that the recovery probability of contained epitopes is maximal and immunogenicity of arising neo-epitopes is minimal.

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Galaxy is an open, web-based platform for data intensive biomedical research. The Galaxy team is a part of BX at Penn State, and the Biology and Mathematics and Computer Science departments at Emory University. The Galaxy Project is supported in part by NHGRI, NSF, The Huck Institutes of the Life Sciences, The Institute for CyberScience at Penn State, and Emory University.