<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rubinstein, Nimrod D</style></author><author><style face="normal" font="default" size="100%">Mayrose, Itay</style></author><author><style face="normal" font="default" size="100%">Martz, Eric</style></author><author><style face="normal" font="default" size="100%">Pupko, Tal</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Epitopia: a web-server for predicting B-cell epitopes.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Artificial Intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Epitopes, B-Lymphocyte</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">287</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.

CONCLUSION: 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.</style></abstract><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19751513?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mayrose, Itay</style></author><author><style face="normal" font="default" size="100%">Penn, Osnat</style></author><author><style face="normal" font="default" size="100%">Erez, Elana</style></author><author><style face="normal" font="default" size="100%">Rubinstein, Nimrod D</style></author><author><style face="normal" font="default" size="100%">Shlomi, Tomer</style></author><author><style face="normal" font="default" size="100%">Freund, Natalia Tarnovitski</style></author><author><style face="normal" font="default" size="100%">Bublil, Erez M</style></author><author><style face="normal" font="default" size="100%">Ruppin, Eytan</style></author><author><style face="normal" font="default" size="100%">Sharan, Roded</style></author><author><style face="normal" font="default" size="100%">Gershoni, Jonathan M</style></author><author><style face="normal" font="default" size="100%">Martz, Eric</style></author><author><style face="normal" font="default" size="100%">Pupko, Tal</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pepitope: epitope mapping from affinity-selected peptides.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Bioinformatics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Binding Sites</style></keyword><keyword><style  face="normal" font="default" size="100%">Epitope Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Peptides</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Binding</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2007 Dec 1</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">23</style></volume><pages><style face="normal" font="default" size="100%">3244-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Identifying the epitope to which an antibody binds is central for many immunological applications such as drug design and vaccine development. The Pepitope server is a web-based tool that aims at predicting discontinuous epitopes based on a set of peptides that were affinity-selected against a monoclonal antibody of interest. The server implements three different algorithms for epitope mapping: PepSurf, Mapitope, and a combination of the two. The rationale behind these algorithms is that the set of peptides mimics the genuine epitope in terms of physicochemical properties and spatial organization. When the three-dimensional (3D) structure of the antigen is known, the information in these peptides can be used to computationally infer the corresponding epitope. A user-friendly web interface and a graphical tool that allows viewing the predicted epitopes were developed. Pepitope can also be applied for inferring other types of protein-protein interactions beyond the immunological context, and as a general tool for aligning linear sequences to a 3D structure. AVAILABILITY: http://pepitope.tau.ac.il/</style></abstract><issue><style face="normal" font="default" size="100%">23</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/17977889?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Landau, Meytal</style></author><author><style face="normal" font="default" size="100%">Mayrose, Itay</style></author><author><style face="normal" font="default" size="100%">Rosenberg, Yossi</style></author><author><style face="normal" font="default" size="100%">Glaser, Fabian</style></author><author><style face="normal" font="default" size="100%">Martz, Eric</style></author><author><style face="normal" font="default" size="100%">Pupko, Tal</style></author><author><style face="normal" font="default" size="100%">Ben-Tal, Nir</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Substitution</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acids</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacterial Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Bayes Theorem</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolution, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Potassium Channels</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005 Jul 1</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">33</style></volume><pages><style face="normal" font="default" size="100%">W299-302</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Key amino acid positions that are important for maintaining the 3D structure of a protein and/or its function(s), e.g. catalytic activity, binding to ligand, DNA or other proteins, are often under strong evolutionary constraints. Thus, the biological importance of a residue often correlates with its level of evolutionary conservation within the protein family. ConSurf (http://consurf.tau.ac.il/) is a web-based tool that automatically calculates evolutionary conservation scores and maps them on protein structures via a user-friendly interface. Structurally and functionally important regions in the protein typically appear as patches of evolutionarily conserved residues that are spatially close to each other. We present here version 3.0 of ConSurf. This new version includes an empirical Bayesian method for scoring conservation, which is more accurate than the maximum-likelihood method that was used in the earlier release. Various additional steps in the calculation can now be controlled by a number of advanced options, thus further improving the accuracy of the calculation. Moreover, ConSurf version 3.0 also includes a measure of confidence for the inferred amino acid conservation scores.</style></abstract><issue><style face="normal" font="default" size="100%">Web Server issue</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/15980475?dopt=Abstract</style></custom1></record></records></xml>