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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

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GECO--linear visualization for comparative genomics.

C T Kuenne¹, R Ghai, T Chakraborty

¹Institute of Medical Microbiology, Justus-Liebig-University Frankfurter Strasse 107, D-35392 Giessen, Germany.

Bioinformatics (Oxford, England)

|November 2, 2006

Summary

GECO software visualizes multiple prokaryotic genomes linearly, aiding in the detection of genomic irregularities. This tool helps researchers identify horizontally transferred genes and other anomalies in microbial genomes.

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Area of Science:

Genomics
Bioinformatics
Microbial Ecology

Background:

Understanding phylogenetic and functional relationships between prokaryotic species requires correlating and displaying qualitative and quantitative data.
Existing methods may lack efficient visualization tools for comparative genomics.

Purpose of the Study:

To present GECO, a novel client/server software for linear visualization of multiple prokaryotic genomes.
To enable the identification of genomic irregularities and evolutionary events in microbial genomes.

Main Methods:

GECO utilizes a client/server architecture to dynamically generate .png or .pdf images for genome visualization.
Ortholog relations are calculated using BLASTCLUST and displayed via color coding.
Genomic irregularities are identified by analyzing anomalous Guanine-Cytosine (G/C) composition.

Main Results:

GECO provides a linear visualization of multiple genomes, facilitating comparative analysis.
The software effectively displays ortholog relationships through color-coded representations.
Anomalous G/C composition can be readily identified, highlighting potential genomic variations.

Conclusions:

GECO is a valuable tool for researchers studying microbial genomics.
The software aids in the detection of horizontally transferred genes, pseudogenes, and insertions/deletions.
GECO enhances the interpretation of phylogenetic and functional relationships in related microbial genomes.