title: Epitopia: a web-server for predicting B-cell epitopes.
abstract: BACKGROUND
  Detecting candidate B-cell epitopes in a protein is a basic and fundamental step in many immunological applications. Due to the impracticality of experimental approaches to systematically scan the entire protein, a computational tool that predicts the most probable epitope regions is desirable.
  
  
  RESULTS
  The Epitopia server is a web-based tool that aims to predict immunogenic regions in either a protein three-dimensional structure or a linear sequence. Epitopia implements a machine-learning algorithm that was trained to discern antigenic features within a given protein. The Epitopia algorithm has been compared to other available epitope prediction tools and was found to have higher predictive power. A special emphasis was put on the development of a user-friendly graphical interface for displaying the results.
  
  
  CONCLUSIONS
  Epitopia is a user-friendly web-server that predicts immunogenic regions for both a protein structure and a protein sequence. Its accuracy and functionality make it a highly useful tool. Epitopia is available at http://epitopia.tau.ac.il and includes extensive explanations and example predictions.
authors.affiliation: Department of Cell Research and Immunology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel. rubi@post.tau.ac.il
authors.forename: Nimrod D
authors.initials: ND
authors.lastname: Rubinstein
authors.forename: Itay
authors.initials: I
authors.lastname: Mayrose
authors.forename: Eric
authors.initials: E
authors.lastname: Martz
authors.forename: Tal
authors.initials: T
authors.lastname: Pupko
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D018985:Epitopes, B-Lymphocyte / Q000737:chemistry*; D020407:Internet; D012984:Software
chemical_list: D018985:Epitopes, B-Lymphocyte