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      DED: Database of Evolutionary Distances

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      Nucleic Acids Research
      Oxford University Press

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          Abstract

          A large database of homologous sequence alignments with good estimates of evolutionary distances can be a valuable resource for molecular evolutionary studies and phylogenetic research in particular. We recently created a database containing 159 921 transcripts from human, mouse, rat, zebrafish and fugu species. Approximately 16 000 homology groups were identified with the help of Ensembl homology evidence. At the macro-level, the database allows us to answer queries of the form:

          1. What is the average k-distance between 5′ untranslated regions of human and mouse?

          2. List the 10 groups with the highest K a/ K s ratio between mouse and rat.

          3. List all identical proteins between human and rat.

          Researchers interested in specific proteins can use a simple web interface to retrieve the homology groups of interest, examine all pairwise distances between members of the group and study the conservation of exon–intron gene structures using a graphical interface. The database is available at http://warta.bio.psu.edu/DED/.

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          Most cited references13

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          The Bioperl toolkit: Perl modules for the life sciences.

          The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.
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            EnsMart: a generic system for fast and flexible access to biological data.

            The EnsMart system (www.ensembl.org/EnsMart) provides a generic data warehousing solution for fast and flexible querying of large biological data sets and integration with third-party data and tools. The system consists of a query-optimized database and interactive, user-friendly interfaces. EnsMart has been applied to Ensembl, where it extends its genomic browser capabilities, facilitating rapid retrieval of customized data sets. A wide variety of complex queries, on various types of annotations, for numerous species are supported. These can be applied to many research problems, ranging from SNP selection for candidate gene screening, through cross-species evolutionary comparisons, to microarray annotation. Users can group and refine biological data according to many criteria, including cross-species analyses, disease links, sequence variations, and expression patterns. Both tabulated list data and biological sequence output can be generated dynamically, in HTML, text, Microsoft Excel, and compressed formats. A wide range of sequence types, such as cDNA, peptides, coding regions, UTRs, and exons, with additional upstream and downstream regions, can be retrieved. The EnsMart database can be accessed via a public Web site, or through a Java application suite. Both implementations and the database are freely available for local installation, and can be extended or adapted to 'non-Ensembl' data sets.
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              An overview of Ensembl.

              Ensembl (http://www.ensembl.org/) is a bioinformatics project to organize biological information around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of individual genomes, and of the synteny and orthology relationships between them. It is also a framework for integration of any biological data that can be mapped onto features derived from the genomic sequence. Ensembl is available as an interactive Web site, a set of flat files, and as a complete, portable open source software system for handling genomes. All data are provided without restriction, and code is freely available. Ensembl's aims are to continue to "widen" this biological integration to include other model organisms relevant to understanding human biology as they become available; to "deepen" this integration to provide an ever more seamless linkage between equivalent components in different species; and to provide further classification of functional elements in the genome that have been previously elusive.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                1 January 2005
                17 December 2004
                : 33
                : Database Issue
                : D442-D446
                Affiliations
                Institute of Molecular Evolutionary Genetics and Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
                Author notes
                [*]

                To whom correspondence should be addressed at Department of Biology, Pennsylvania State University, 514 Mueller Lab, University Park, PA 16802, USA. Tel: +1 814 865 5025; Fax: +1 814 865 9366; Email: wojtek@ 123456psu.edu

                [a]

                The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use permissions, please contact journals.permissions@ 123456oupjournals.org .

                [a]

                © 2005, the authors

                Article
                gki094
                10.1093/nar/gki094
                540048
                15608234
                6617a679-6d11-4665-9d26-75db2cf34559
                Copyright © 2005 Oxford University Press
                History
                : 15 August 2004
                : 12 October 2004
                : 12 October 2004
                Categories
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                Genetics
                Genetics

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