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IMG ER: A System for Microbial Genome Annotation Expert Review and Curation

Description: A rapidly increasing number of microbial genomes are sequenced by organizations worldwide and are eventually included into various public genome data resources. The quality of the annotations depends largely on the original dataset providers, with erroneous or incomplete annotations often carried over into the public resources and difficult to correct. We have developed an Expert Review (ER) version of the Integrated Microbial Genomes (IMG) system, with the goal of supporting systematic and efficient revision of microbial genome annotations. IMG ER provides tools for the review and curation of annotations of both new and publicly available microbial genomes within IMG's rich integrated genome framework. New genome datasets are included into IMG ER prior to their public release either with their native annotations or with annotations generated by IMG ER's annotation pipeline. IMG ER tools allow addressing annotation problems detected with IMG's comparative analysis tools, such as genes missed by gene prediction pipelines or genes without an associated function. Over the past year, IMG ER was used for improving the annotations of about 150 microbial genomes.
Date: May 25, 2009
Creator: Markowitz, Victor M.; Mavromatis, Konstantinos; Ivanova, Natalia N.; Chen, I-Min A.; Chu, Ken & Kyrpides, Nikos C.
Partner: UNT Libraries Government Documents Department

The integrated microbial genomes (IMG) system in 2007: datacontent and analysis tool extensions

Description: The Integrated Microbial Genomes (IMG) system is a data management, analysis and annotation platform for all publicly available genomes. IMG contains both draft and complete JGI microbial genomes integrated with all other publicly available genomes from all three domains of life, together with a large number of plasmids and viruses. IMG provides tools and viewers for analyzing and annotating genomes, genes and functions, individually or in a comparative context. Since its first release in 2005, IMG's data content and analytical capabilities have been constantly expanded through quarterly releases. IMG is provided by the DOE-Joint Genome Institute (JGI) and is available from http://img.jgi.doe.gov.
Date: August 1, 2007
Creator: Markowitz, Victor M.; Szeto, Ernest; Palaniappan, Krishna; Grechkin, Yuri; Chu, Ken; Chen, I-Min A. et al.
Partner: UNT Libraries Government Documents Department

IMG/M: A data management and analysis system for metagenomes

Description: IMG/M is a data management and analysis system for microbial community genomes (metagenomes) hosted at the Joint Genome Institute (JGI). IMG/M consists of metagenome data integrated with isolate microbial genomes from the Integrated Microbial Genomes (IMG) system. IMG/M provides IMG's comparative data analysis tools extended to handle metagenome data, together with metagenome-specific analysis tools. IMG/M is available at http://img.jgi.doe.gov/m. Studies of the collective genomes (also known as metagenomes) of environmental microbial communities (also known as microbiomes) are expected to lead to advances in environmental cleanup, agriculture, industrial processes, alternative energy production, and human health (1). Metagenomes of specific microbiome samples are sequenced by organizations worldwide, such as the Department of Energy's (DOE) Joint Genome Institute (JGI), the Venter Institute and the Washington University in St. Louis using different sequencing strategies, technology platforms, and annotation procedures. According to the Genomes OnLine Database, about 28 metagenome studies have been published to date, with over 60 other projects ongoing and more in the process of being launched (2). The Department of Energy's (DOE) Joint Genome Institute (JGI) is one of the major contributors of metagenome sequence data, currently sequencing more than 50% of the reported metagenome projects worldwide. Due to the higher complexity, inherent incompleteness, and lower quality of metagenome sequence data, traditional assembly, gene prediction, and annotation methods do not perform on these datasets as well as they do on isolate microbial genome sequences (3, 4). In spite of these limitations, metagenome data are amenable to a variety of analyses, as illustrated by several recent studies (5-10). Metagenome data analysis is usually set up in the context of reference isolate genomes and considers the questions of composition and functional or metabolic potential of individual microbiomes, as well as differences between microbiome samples. Such analysis relies on efficient management of genome and metagenome ...
Date: August 1, 2007
Creator: Markowitz, Victor M.; Ivanova, Natalia N.; Szeto, Ernest; Palaniappan, Krishna; Chu, Ken; Dalevi, Daniel et al.
Partner: UNT Libraries Government Documents Department