The comprehensive microbial resource

By Tanja Davidsen, Erin Beck, A. Ganapathy, R. Montgomery, Nikhat Zafar, Qi Yang, R. Madupu, Phil Goetz, K. Galinsky, Owen White and 1 more. Nucleic Acids Res., 2000

334 citations recorded by the source corpus.

The Comprehensive Microbial Resource or CMR (http://cmr.jcvi.org) provides a web-based central resource for the display, search and analysis of the sequence and annotation for complete and publicly available bacterial and archaeal genomes. In addition to displaying the original annotation from GenBank, the CMR makes available secondary automated structural and functional annotation across all genomes to provide consistent data types necessary for effective mining of genomic data. Precomputed homology searches are stored to allow meaningful genome comparisons. The CMR supplies users with over 50 different tools to utilize the sequence and annotation data across one or more of the 571 currently available genomes. At the gene level users can view the gene annotation and underlying evidence. Genome level information includes whole genome graphical displays, biochemical pathway maps and genome summary data. Comparative tools display analysis between genomes with homology and genome alignment tools, and searches across the accessions, annotation, and evidence assigned to all genes/genomes are available. The data and tools on the CMR aid genomic research and analysis, and the CMR is included in over 200 scientific publications. The code underlying the CMR website and the CMR database are freely available for download with no license restrictions.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/18d91f64fc4ad9dc77e658f21ba068d294e2715b

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Citations in the corpus

Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution (2008, neutral): “…attention has been devoted to the dependence of evolutionary rate, particularly dN, on the breadth, tissue specificity , and aggregate level of expression in multicellular organisms (Duret and Mouchiroud, 2000; Liao et al., 2006; Pá l et al., 2006; Parmley et al., 2007; Wright et al., 2004).”
BIGSdb: Scalable analysis of bacterial genome variation at the population level (2010, background): “Many of the genomes hosted in online databases [42-44] have detailed and comprehensive annotation, but what these databases have in common is that for any particular species they contain very few genomes (Figure 4) and the analysis is geared specifically to the attributes of the sequence itself rath”
TIGRFAMs and Genome Properties in 2013 (2012, methodology): “Genome Properties is now hosted independently of the CMR.”
The MetaCyc Database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases (2007, methodology): “The third category, generation of precursor metabolites and energy, contains 100 pathways, with the largest classes being fermentation (25), respiration (17), chemoautotrophic energy metabolism (14) and methanogenesis (13).”
The UniProt-GO Annotation database in 2011 (2011, methodology): “The UniProt GO annotations are supplemented with those from 36 external groups [annotations from the PAMGO (6), EcoCyc (7), EcoWiki (8), JCVI (9) and CGD (10) have been added to the data set since 2009], ensuring that all manual annotations from GO Consortium members that can be mapped to a UniProtK”
EDGAR: A software framework for the comparative analysis of prokaryotic genomes (2009, methodology): “Therefore databases like the Comprehensive Microbial Resource (CMR) or the Microbial Genome Database (MBGD) were designed dedicated to the comparison of multiple genomes of related species [ 12 ,13].”