IMG: the integrated microbial genomes database and comparative analysis system

By Victor M. Markowitz, I-Min A. Chen, Krishna Palaniappan, Ken Chu, Ernest Szeto, Y. Grechkin, Anna Ratner, Biju Jacob, Jinghua Huang, P. Williams and 5 more. Nucleic Acids Res., 2011

1,354 citations recorded by the source corpus.

The Integrated Microbial Genomes (IMG) system serves as a community resource for comparative analysis of publicly available genomes in a comprehensive integrated context. IMG integrates publicly available draft and complete genomes from all three domains of life with a large number of plasmids and viruses. IMG provides tools and viewers for analyzing and reviewing the annotations of genes and genomes in a comparative context. IMG's data content and analytical capabilities have been continuously extended through regular updates since its first release in March 2005. IMG is available at http://img.jgi.doe.gov. Companion IMG systems provide support for expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er), teaching courses and training in microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu) and analysis of genomes related to the Human Microbiome Project (IMG/HMP: http://www.hmpdacc-resources.org/img_hmp).

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2f5f552e29e5bf1a5ca19088dc5aebc713d51fe9

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Citations in the corpus

Computational meta'omics for microbial community studies (2013, background): “Consequently, a reference set of microbial genomes on the order of 5000 ﬁnished or high-quality sequences are now available (Markowitz et al , 2012a), describing more than 2000 species, and these numbers are quickly increasing.”
Microbial species delineation using whole genome sequences (2015, methodology): “Here, we augment this approach and have developed a scalable method to compute gANI for 86.5 million genome pairs in the publicly available Integrated Microbial Genomes (IMG) database (5).”
Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences (2013, methodology): “To do this, PICRUSt uses existing annotations of gene content and 16S copy number from reference bacterial and archaeal genomes in the IMG database 25 .”
EDGAR 2.0: an enhanced software platform for comparative gene content analyses (2016, neutral): “Several software platforms for comparative gene content analyses have been developed in the last decade like IMG (3), MicrobesOnline (4), MBGD (5) or OrtholugeDB (6).”
Growth enhancement and drought tolerance of hybrid poplar upon inoculation with endophyte consortia (2016, methodology): “Annotations and comparative analysis of all genomes is available through the Integrated Microbial Genome system [47].”
IMG/M: integrated genome and metagenome comparative data analysis system (2016, methodology): “The Compare Genomes menu provides many comparative analysis tools including Genome Statistics, Synteny Viewers, Phylogenetic Distribution, Distance Tree, Function Profile, Genome Clustering, Best Homologs and Phylogenetic Marker COGs (28,30), as well as newly added Average Nucleotide Identity (ANI) ”
Metabolic modeling of species interaction in the human microbiome elucidates community-level assembly rules (2013, methodology): “Because MetaPhlAn does not identify taxa at the strain level, representative genomes were selected from IMG.”
Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. (2014, methodology): “Genome Sequences A set of 1,154 complete genome sequences was obtained from JGI-IMG (Markowitz et al., 2012), version 3.”
High-Specificity Targeted Functional Profiling in Microbial Communities with ShortBRED (2015, methodology): “Each row is a class, each column is sample from the HMP and the value in each cell equals [ShortBRED Count in RPKM—Sum(Bacterial Genome's Abundance in Sample Median ShortBRED AR Count Across Copies of Bacterial Genome in our 3,305 isolates from IMG.]”
Untangling the Genetic Basis of Fibrolytic Specialization by Lachnospiraceae and Ruminococcaceae in Diverse Gut Communities (2013, methodology): “Comparative Analysis of Sugar Transport Genes Genomes from each member of the Lachnospiraceae, Clostridiaceae, and Ruminococcaceae found in the IMG database [27] were compared in terms of numbers of carbohydrate transport genes.”
BugBase predicts organism-level microbiome phenotypes (2017, methodology): “Alignments of each open-reading frame against all genomes within IMG were performed with USEARCH, using the ‘usearch_global’ parameter with an ID match of 0.6 and a query coverage of 0.8 [36].”