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      RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes

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          Abstract

          The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.

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          ISfinder: the reference centre for bacterial insertion sequences

          ISfinder () is a dedicated database for bacterial insertion sequences (ISs). It has superseded the Stanford reference center. One of its functions is to assign IS names and to provide a focal point for a coherent nomenclature. It is also the repository for ISs. Each new IS is indexed together with information such as its DNA sequence and open reading frames or potential coding sequences, the sequence of the ends of the element and target sites, its origin and distribution together with a bibliography where available. Another objective is to continuously monitor ISs to provide updated comprehensive groupings or families and to provide some insight into their phylogenies. The site also contains extensive background information on ISs and transposons in general. Online tools are gradually being added. At present an online Blast facility against the entire bank is available. But additional features will include alignment capability, PsiBLAST and HMM profiles. ISfinder also includes a section on bacterial genomes and is involved in annotating the IS content of these genomes. Finally, this database is currently recommended by several microbiology journals for registration of new IS elements before their publication.
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            The comprehensive antibiotic resistance database.

            The field of antibiotic drug discovery and the monitoring of new antibiotic resistance elements have yet to fully exploit the power of the genome revolution. Despite the fact that the first genomes sequenced of free living organisms were those of bacteria, there have been few specialized bioinformatic tools developed to mine the growing amount of genomic data associated with pathogens. In particular, there are few tools to study the genetics and genomics of antibiotic resistance and how it impacts bacterial populations, ecology, and the clinic. We have initiated development of such tools in the form of the Comprehensive Antibiotic Research Database (CARD; http://arpcard.mcmaster.ca). The CARD integrates disparate molecular and sequence data, provides a unique organizing principle in the form of the Antibiotic Resistance Ontology (ARO), and can quickly identify putative antibiotic resistance genes in new unannotated genome sequences. This unique platform provides an informatic tool that bridges antibiotic resistance concerns in health care, agriculture, and the environment.
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              ARDB—Antibiotic Resistance Genes Database

              The treatment of infections is increasingly compromised by the ability of bacteria to develop resistance to antibiotics through mutations or through the acquisition of resistance genes. Antibiotic resistance genes also have the potential to be used for bio-terror purposes through genetically modified organisms. In order to facilitate the identification and characterization of these genes, we have created a manually curated database—the Antibiotic Resistance Genes Database (ARDB)—unifying most of the publicly available information on antibiotic resistance. Each gene and resistance type is annotated with rich information, including resistance profile, mechanism of action, ontology, COG and CDD annotations, as well as external links to sequence and protein databases. Our database also supports sequence similarity searches and implements an initial version of a tool for characterizing common mutations that confer antibiotic resistance. The information we provide can be used as compendium of antibiotic resistance factors as well as to identify the resistance genes of newly sequenced genes, genomes, or metagenomes. Currently, ARDB contains resistance information for 13 293 genes, 377 types, 257 antibiotics, 632 genomes, 933 species and 124 genera. ARDB is available at http://ardb.cbcb.umd.edu/.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                10 February 2015
                2015
                : 5
                : 8365
                Affiliations
                [1 ]Computing, Environment and Life Sciences , Argonne National Laboratory, Argonne IL, 60439, USA
                [2 ]Computation Institute, University of Chicago , Chicago, Illinois, 60637, USA
                [3 ]Fellowship for Interpretation of Genomes, Burr Ridge , IL, 60527, USA
                [4 ]Mathematics and Computer Science Division, Argonne National Laboratory , Argonne, IL, 60439, USA
                [5 ]Department of Computer Science, San Diego State University , San Diego, California, 92182, USA
                [6 ]Department of Microbiology, University of Illinois at Urbana-Champaign , Urbana, IL, 61801, USA
                [7 ]Virginia Bioinformatics Institute, Virginia Tech University , Blacksburg, VA, 24060, USA
                [8 ]USDA-ARS Laboratory at Cold Spring Harbor Laboratory , Cold Spring Harbor NY, 11724, USA
                [9 ]Department of Computer Science, University of Chicago , Chicago, Illinois, 60637, USA
                Author notes
                Article
                srep08365
                10.1038/srep08365
                4322359
                25666585
                9b9e83e2-5759-4c39-a25f-3658b3c18940
                Copyright © 2015, Macmillan Publishers Limited. All rights reserved

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/

                History
                : 12 November 2014
                : 02 January 2015
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