Published online 18 May 2012 Nucleic Acids Research, 2012, Vol. 40, Web Server issue W525–W530 doi:10.1093/nar/gks438 Immune epitope database analysis resource Yohan Kim1, Julia Ponomarenko 2 , Zhanyang Zhu 3 , Dorjee Tamang 1 , Peng Wang 4 , Jason Greenbaum1, Claus Lundegaard5, Alessandro Sette1, Ole Lund 5 , Philip E. Bourne2, Morten Nielsen5 and Bjoern Peters1,* 1La Jolla Institute for Allergy and Immunology, 9420 Athena Circle, La Jolla, CA 92037, 2San Diego Supercomputer Center, MC 0505, 10100 Hopkins Drive, La Jolla, CA 92093, 3Sequenom, 3595 John Hopkins Court, San Diego, CA 92121, USA, 4Shanghai Advanced Research Institute, No.99 Haike Road, Zhangjiang Hi-Tech Park, Pudong Shanghai, 201210, China and 5Technical University of Denmark, Building 208, 2800, Lyngby, Denmark Received March 2, 2012; Revised April 19, 2012; Accepted April 25, 2012 ABSTRACT The immune epitope database analysis resource (IEDB-AR: http://tools.iedb.org) is a collection of tools for prediction and analysis of molecular targets of T- and B-cell immune responses (i.e. epi- topes). Since its last publication in the NAR webserver issue in 2008, a new generation of peptide:MHC binding and T-cell epitope predictive tools have been added. As validated by different labs and in the first international competition for predicting peptide:MHC-I binding, their predictive performances have improved considerably. In addition, a new B-cell epitope prediction tool was added, and the homology mapping tool was updated to enable mapping of discontinuous epitopes onto 3D structures. Furthermore, to serve a wider range of users, the number of ways in which IEDB-AR can be accessed has been expanded. Specifically, the predictive tools can be program- matically accessed using a web interface and can also be downloaded as software packages. INTRODUCTION The immune system orchestrates various classes of mol- ecules to detect an abnormal state of the host, as a ﬁrst step toward the goal of protecting the host from diseases. To achieve such detection, dedicated molecules such as major histocompatibility complexes (MHCs), T-cell recep- tors (TCRs) and B-cell receptors (BCRs) continuously scan cellular surfaces and extra-intra-cellular spaces for non-self molecules and trigger immune responses upon their detection. Parts of such non-self molecules (e.g. proteins, carbohydrates and other macromolecules) recognized by the immune system are called epitopes. Depending on the context of immune epitope recogni- tion, different kinds of immune responses are initiated. For instance, TCRs binding peptide:MHC-I (class I) complexes presented on the cell surface are associated with cytotoxic lymphocyte activity (i.e. cell killing); whereas, TCRs binding peptide:MHC-II (class II) com- plexes are associated with recruiting helper T-cells and alerting B-cells. Thus, improved molecular-level under- standing of immune epitope recognition will further enhance the development of novel vaccines, diagnostics and therapeutics in treating infectious and autoimmune diseases, allergies and cancers. To address this need, the immune epitope database- analysis resource (IEDB-AR) aims to be the premier resource in providing web-based tools for immune epitope predictions and analyses. Since its publication in the NAR webserver issue in 2008 (1), major updates and the addition of new predictive tools have been made. Speciﬁcally, six new peptide:MHC binding, one antigen processing and one B-cell epitope predictive tool have been added. In addition, binding afﬁnity data for MHC-I and MHC-II molecules have been signiﬁcantly expanded, resulting in both increased coverage of alleles and improved accuracy for existing predictors. THE WEB RESOURCE Tools provided on the IEDB analysis resource website can be grouped into those that make predictions or carry out analyses (Table 1). Predictive tools can be further grouped based on their targeted immune recognition contexts: (i) peptide:MHC binding, (ii) antigen processing and (iii) B-cell-receptor/antibody binding. Since the last *To whom correspondence should be addressed. Tel: +1 858 752 6914; Fax: +1 858 752 6987; Email: bpeters@liai.org The Author(s) 2012. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.