@article {443,
	title = {De Novo assembly of the complete genome of an enhanced electricity-producing variant of Geobacter sulfurreducens using only short reads.},
	journal = {PLoS One},
	volume = {5},
	year = {2010},
	month = {2010},
	pages = {e10922},
	abstract = {State-of-the-art DNA sequencing technologies are transforming the life sciences due to their ability to generate nucleotide sequence information with a speed and quantity that is unapproachable with traditional Sanger sequencing. Genome sequencing is a principal application of this technology, where the ultimate goal is the full and complete sequence of the organism of interest. Due to the nature of the raw data produced by these technologies, a full genomic sequence attained without the aid of Sanger sequencing has yet to be demonstrated.We have successfully developed a four-phase strategy for using only next-generation sequencing technologies (Illumina and 454) to assemble a complete microbial genome de novo. We applied this approach to completely assemble the 3.7 Mb genome of a rare Geobacter variant (KN400) that is capable of unprecedented current production at an electrode. Two key components of our strategy enabled us to achieve this result. First, we integrated the two data types early in the process to maximally leverage their complementary characteristics. And second, we used the output of different short read assembly programs in such a way so as to leverage the complementary nature of their different underlying algorithms or of their different implementations of the same underlying algorithm.The significance of our result is that it demonstrates a general approach for maximizing the efficiency and success of genome assembly projects as new sequencing technologies and new assembly algorithms are introduced. The general approach is a meta strategy, wherein sequencing data are integrated as early as possible and in particular ways and wherein multiple assembly algorithms are judiciously applied such that the deficiencies in one are complemented by another.},
	keywords = {Algorithms, Electricity, Genome, Bacterial, Geobacter, Polymerase Chain Reaction},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0010922},
	author = {Nagarajan, Harish and Butler, Jessica E and Klimes, Anna and Qiu, Yu and Zengler, Karsten and Ward, Joy and Young, Nelson D and Meth{\'e}, Barbara A and Palsson, Bernhard {\O} and Lovley, Derek R and Barrett, Christian L}
}
@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}
}
@article {1218,
	title = {Determination of polydextrose in foods by ion chromatography: collaborative study.},
	journal = {J AOAC Int},
	volume = {84},
	year = {2001},
	month = {2001 Mar-Apr},
	pages = {472-8},
	abstract = {<p>Eight collaborating laboratories assayed 7 blind duplicate pairs of foods for polydextrose content. The 7 test sample pairs ranged from low (2\%) to high (95\%) levels. The following foods were prepared with polydextrose mixed into the other ingredients and then baked, cooked, or otherwise prepared: milk chocolate candy, iced tea, sugar cookie, grape jelly, soft jellied candy, and powdered drink mix. Collaborators received a polydextrose standard to develop a calibration curve. The method determined polydextrose by ion chromatography, after removal of interfering food components (high molecular weight solubles). Repeatability standard deviations (RSDr) ranged from 3.93 to 9.04\%; reproducibility standard deviations (RSDR) ranged from 4.48 to 14.06\%. The average recovery was 94\%.</p>},
	keywords = {Algorithms, Beverages, Cacao, Candy, Chromatography, Ion Exchange, Food Analysis, Glucans, Indicators and Reagents, Reference Standards, Tea, Ultracentrifugation},
	issn = {1060-3271},
	author = {Craig, S A and Holden, J F and Khaled, M Y}
}
