MaGe: a microbial genome annotation system supported by synteny results

By D. Vallenet, Laurent Labarre, Zoé Rouy, V. Barbe, S. Bocs, S. Cruveiller, Aurélie Lajus, G. Pascal, Claude Scarpelli, C. Médigue. Nucleic Acids Research, 2006

404 citations recorded by the source corpus.

Magnifying Genomes (MaGe) is a microbial genome annotation system based on a relational database containing information on bacterial genomes, as well as a web interface to achieve genome annotation projects. Our system allows one to initiate the annotation of a genome at the early stage of the finishing phase. MaGe's main features are (i) integration of annotation data from bacterial genomes enhanced by a gene coding re-annotation process using accurate gene models, (ii) integration of results obtained with a wide range of bioinformatics methods, among which exploration of gene context by searching for conserved synteny and reconstruction of metabolic pathways, (iii) an advanced web interface allowing multiple users to refine the automatic assignment of gene product functions. MaGe is also linked to numerous well-known biological databases and systems. Our system has been thoroughly tested during the annotation of complete bacterial genomes (Acinetobacter baylyi ADP1, Pseudoalteromonas haloplanktis, Frankia alni) and is currently used in the context of several new microbial genome annotation projects. In addition, MaGe allows for annotation curation and exploration of already published genomes from various genera (e.g. Yersinia, Bacillus and Neisseria). MaGe can be accessed at .

Subfields: Ecology, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/7d5b410146bbe35a8ffa89dee4cf4f96bc49da73

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Genetics

In Molecular Biology

Citations in the corpus

Genome Majority Vote Improves Gene Predictions (2011, positive): “Newer maps may include information from servers such as MaGe [12], RAST [8], or GenePRIMP [9] that use comparative genomics methods for genome annotation, including leveraging information from experimentally validated gene starts.”
A Nitrospira metagenome illuminates the physiology and evolution of globally important nitrite-oxidizing bacteria (2010, methodology): “The MaGe software system (42) was used for the prediction, automatic annotation, and manual annotation refinement of all CDS as described in SI Materials and Methods.”
The RAST Server: Rapid Annotations using Subsystems Technology (2008, background): “This has led to the obvious conclusion that most of the annotations that will be associated with these newly-sequenced genomes will be provided through technologies that are largely automated, and a growing number of efforts focusing on different aspects of automated annotation have emerged [1-6].”
IMG ER: a system for microbial genome annotation expert review and curation (2009, neutral): “Contact: vmmarkowitz@lbl.gov Supplementary information: Supplementary data are available at Bioinformatics online.”
BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions (2010, background): “Because of the great effort involved, there have been attempts to partially automate the process [25-31] and split work through collaboration [32].”
Organised Genome Dynamics in the Escherichia coli Species Results in Highly Diverse Adaptive Paths (2009, methodology): “coli K-12 MG1655 orthologous gene annotations [96] if any, or to similarity results obtained using the MicroScope analysis pipeline described in [95].”
MicroScope—an integrated microbial resource for the curation and comparative analysis of genomic and metabolic data (2012, methodology): “Genomes may be compared in terms of gene content via the ‘Gene Phyloproﬁle’ tool, which uses pre-computed homologies and synteny groups (1).”