@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 {679,
	title = {Proteopedia.Org: a scientific "Wiki" bridging the rift between 3D structure and function of biomacromolecules.},
	journal = {Biopolymers},
	volume = {92},
	year = {2009},
	month = {2009},
	pages = {76-7},
	keywords = {Computational Biology, Imaging, Three-Dimensional, Internet, Models, Molecular, Protein Structure, Quaternary, Protein Structure, Tertiary, Proteins, Structure-Activity Relationship},
	issn = {0006-3525},
	doi = {10.1002/bip.21126},
	author = {Martz, Eric}
}
@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}
}
@article {685,
	title = {Protein Explorer: easy yet powerful macromolecular visualization.},
	journal = {Trends Biochem Sci},
	volume = {27},
	year = {2002},
	month = {2002 Feb},
	pages = {107-9},
	abstract = {Protein Explorer (PE, http://www.proteinexplorer.org) enables students, educators and other nonspecialists to visualize macromolecular structures easily. It also offers several advanced capabilities useful to protein structure specialists. Great attention has been given to making PE easy to use. Explanations, color keys and troubleshooting information are displayed automatically. There are also {\textquoteright}Frequently Asked Questions{\textquoteright}, a one-hour {\textquoteright}Quick-Tour{\textquoteright}, an alphabetical {\textquoteright}Help/Index/Glossary{\textquoteright}, and a detailed {\textquoteright}Tutorial{\textquoteright}; all making PE much easier to use than either Chime or RasMol. Moreover, it is much more powerful; in addition to basic macromolecular visualization capabilities common to most similar programs, it offers one-click visualization of interfaces between moieties ({\textquoteright}contacts{\textquoteright}), cation-pi interactions and salt bridges, as well as easy-to-use routines to visualize regions of conservation in three-dimensional protein structures based on multiple sequence alignments.},
	keywords = {Computational Biology, DNA, Evolution, Molecular, Macromolecular Substances, Protein Structure, Secondary, Proteins, Sequence Alignment, Software},
	issn = {0968-0004},
	author = {Martz, Eric}
}
