scholarly journals MicroScope: a platform for microbial genome annotation and comparative genomics

Database ◽  
2009 ◽  
Vol 2009 ◽  
Author(s):  
D. Vallenet ◽  
S. Engelen ◽  
D. Mornico ◽  
S. Cruveiller ◽  
L. Fleury ◽  
...  
Keyword(s):  
Comparative Genomics ◽  
Genome Annotation ◽  
Microbial Genome

scholarly journals The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4)

2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Marcel Huntemann ◽  
Natalia N. Ivanova ◽  
Konstantinos Mavromatis ◽  
H. James Tripp ◽  
David Paez-Espino ◽  
...  
Keyword(s):  
Operating Procedure ◽  
Genome Annotation ◽  
Standard Operating Procedure ◽  
Microbial Genome ◽  
Annotation Pipeline ◽  
Standard Operating

scholarly journals IMG ER: a system for microbial genome annotation expert review and curation

2009 ◽  
Vol 25 (17) ◽  
pp. 2271-2278 ◽  
Author(s):  
Victor M. Markowitz ◽  
Konstantinos Mavromatis ◽  
Natalia N. Ivanova ◽  
I-Min A. Chen ◽  
Ken Chu ◽  
...  
Keyword(s):  
Genome Annotation ◽  
Microbial Genome ◽  
Expert Review

Automated Genome Annotation and Comparative Genomics

Biotechnology ◽  
2008 ◽  
pp. 361-378
Author(s):  
Shuba Gopal ◽  
Terry Gaasterland
Keyword(s):  
Comparative Genomics ◽  
Genome Annotation

scholarly journals Integration of Data in Pathogenomics: Three Layers of cellular complexity and an XML-based Framework

2004 ◽  
Vol 1 (1) ◽  
pp. 52-63
Author(s):  
M. Dünßer ◽  
R. Lampidis ◽  
S. Schmidt ◽  
D. Seipel ◽  
T. Dandekar
Keyword(s):  
Comparative Genomics ◽  
Data Integration ◽  
Genome Annotation ◽  
Regulatory Elements ◽  
Protein Domain ◽  
Mode Analysis ◽  
Sequence Annotation ◽  
Elementary Mode Analysis ◽  
Metabolic Network Analysis ◽  
Domain Annotation

Summary Integration of data in pathogenomics is achieved here considering three different levels of cellular complexity: (i) genome and comparative genomics, (ii) enzyme cascades and pathway analysis, (iii) networks including metabolic network analysis.After direct sequence annotation exploiting tools for protein domain annotation (e.g. AnDOM) and analysis of regulatory elements (e.g. the RNA analyzer tool) the analysis results from extensive comparative genomics are integrated for the first level, pathway alignment adds data for the pathway level, elementary mode analysis and metabolite databanks add to the third level of cellular complexity. For efficient data integration of all data the XML based platform myBSMLStudio2003 is discussed and developed here. It integrates XQuery capabilities, automatic scripting updates for sequence annotation and a JESS expert system shell for functional annotation. In the context of genome annotation platforms in place (GenDB, PEDANT) these different tools and approaches presented here allow improved functional genome annotation as well as data integration in pathogenomics.

scholarly journals Microbial genome analysis: the COG approach

2017 ◽  
Vol 20 (4) ◽  
pp. 1063-1070 ◽  
Author(s):  
Michael Y Galperin ◽  
David M Kristensen ◽  
Kira S Makarova ◽  
Yuri I Wolf ◽  
Eugene V Koonin
Keyword(s):  
Genome Analysis ◽  
Metabolic Pathways ◽  
Genome Annotation ◽  
Functional Characterization ◽  
Microbial Genome ◽  
Functional Categories ◽  
Orthologous Genes ◽  
Microbial Genomes ◽  
The Past

Abstract For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis.

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