@article {678,
	title = {Epitopia: a web-server for predicting B-cell epitopes.},
	journal = {BMC Bioinformatics},
	volume = {10},
	year = {2009},
	month = {2009},
	pages = {287},
	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.

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.},
	keywords = {Algorithms, Artificial Intelligence, Computational Biology, Epitopes, B-Lymphocyte, Internet, Software},
	issn = {1471-2105},
	doi = {10.1186/1471-2105-10-287},
	author = {Rubinstein, Nimrod D and Mayrose, Itay and Martz, Eric and Pupko, Tal}
}
@article {681,
	title = {Pepitope: epitope mapping from affinity-selected peptides.},
	journal = {Bioinformatics},
	volume = {23},
	year = {2007},
	month = {2007 Dec 1},
	pages = {3244-6},
	abstract = {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/},
	keywords = {Algorithms, Amino Acid Sequence, Binding Sites, Epitope Mapping, Molecular Sequence Data, Peptides, Protein Binding, Sequence Alignment, Sequence Analysis, Protein, Software},
	issn = {1367-4811},
	doi = {10.1093/bioinformatics/btm493},
	author = {Mayrose, Itay and Penn, Osnat and Erez, Elana and Rubinstein, Nimrod D and Shlomi, Tomer and Freund, Natalia Tarnovitski and Bublil, Erez M and Ruppin, Eytan and Sharan, Roded and Gershoni, Jonathan M and Martz, Eric and Pupko, Tal}
}
@article {682,
	title = {Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach.},
	journal = {Nucleic Acids Res},
	volume = {35},
	year = {2007},
	month = {2007 Jul},
	pages = {W506-11},
	abstract = {Biologically significant sites in a protein may be identified by contrasting the rates of synonymous (K(s)) and non-synonymous (K(a)) substitutions. This enables the inference of site-specific positive Darwinian selection and purifying selection. We present here Selecton version 2.2 (http://selecton.bioinfo.tau.ac.il), a web server which automatically calculates the ratio between K(a) and K(s) (omega) at each site of the protein. This ratio is graphically displayed on each site using a color-coding scheme, indicating either positive selection, purifying selection or lack of selection. Selecton implements an assembly of different evolutionary models, which allow for statistical testing of the hypothesis that a protein has undergone positive selection. Specifically, the recently developed mechanistic-empirical model is introduced, which takes into account the physicochemical properties of amino acids. Advanced options were introduced to allow maximal fine tuning of the server to the user{\textquoteright}s specific needs, including calculation of statistical support of the omega values, an advanced graphic display of the protein{\textquoteright}s 3-dimensional structure, use of different genetic codes and inputting of a pre-built phylogenetic tree. Selecton version 2.2 is an effective, user-friendly and freely available web server which implements up-to-date methods for computing site-specific selection forces, and the visualization of these forces on the protein{\textquoteright}s sequence and structure.},
	keywords = {Algorithms, Amino Acid Sequence, Amino Acid Substitution, Amino Acids, Animals, Bayes Theorem, Computational Biology, Computer Simulation, Humans, Internet, Models, Molecular, Molecular Sequence Data, Phylogeny, Proteins, Sequence Analysis, Protein, Software},
	issn = {1362-4962},
	doi = {10.1093/nar/gkm382},
	author = {Stern, Adi and Doron-Faigenboim, Adi and Erez, Elana and Martz, Eric and Bacharach, Eran and Pupko, Tal}
}
