WORLDCOMP'07 Tutorial

IMG (http://img.jgi.doe.gov) is a microbial genome analysis system developed at the DOE Joint Genome Institute (JGI) to promote individual and comparative analysis of genomes sequenced at the JGI and elsewhere. Version 2.1, released on March, 2007, contains 2782 genomes from all domains of life and plasmids. The IMG user interface allows navigating the microbial genome data space along its three key dimensions (genes, genomes, and functions), and groups together the main comparative analysis tools. Microbial genome data analysis in IMG usually starts with the definition of an analysis context in terms of selected genomes, functional annotations, and/or genes, followed by the individual or comparative analysis of genomes, functional annotations, or genes. Users may also add their own gene product name to a list of selected genes. Overall, IMG aims to provide a framework for comparative analysis of the genomes sequenced by the Joint Genome Institute. Its goal is to facilitate the visualization and exploration of genomes from a functional and evolutionary perspective.

The objective of the tutorial is to present the functionality of IMG tools and methods that facilitate the analysis of genomes in a comparative context.

This tutorial is intended for scientists, and graduate students who are interested in comparative genomics and gene annotation.

Konstantinos Mavrommatis is a postdoctoral associate with the Genome Biology Program in the DOE Joint Genome Institute since 2004. He participates in genomic and metagenomic analysis projects and the development of the Integrated Microbial Genomes (IMG) system. He received his Degree in Biology from the Kapodistrian University of Athens, Greece, and his Masters in Biotechnology and Ph.D in Molecular Biology and Biomedicine from the University of Crete, Greece. His work focused on the structural adaptation of enzymes from cold adapted bacteria.

His research interests include identification of non-coding RNAs in bacterial genomes, function prediction and annotation of genes using fusion events and chromosomal neighborhood correlation and development and benchmarking of metagenomic analysis pipelines.