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09:40
Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
Published on: June 11, 2015
Comparative phyloinformatics of virus genes at micro and macro levels in a distributed computing environment
Dadabhai T Singh1, Rahul Trehan, Bertil Schmidt
1Genvea Biosciences, 53 Craig Road, #04-01, Singapore 089691. dtsingh@genvea.com
BMC Bioinformatics
|March 20, 2008
Summary
This study introduces Quascade, a user-friendly system for distributed comparative phyloinformatics, enabling efficient virus evolution analysis. H5N1 neuraminidase analysis reveals geographical clustering, highlighting Quascade
Area of Science:
- Computational Biology
- Virology
- Bioinformatics
Background:
- Global pandemic preparedness necessitates monitoring emerging viral subtypes like influenza A H5N1.
- Comparative phyloinformatics offers tools for virus evolution analysis but faces computational and expertise barriers.
- Current limitations include the need for specialized teams and prohibitive runtimes on sequential platforms.
Purpose of the Study:
- To present Quascade, a graphical workflow system for efficient comparative phyloinformatics.
- To demonstrate the application of Quascade in a distributed computing environment for virus analysis.
- To analyze the phylogenetic patterns of H5N1 neuraminidase at micro and macro levels.
Main Methods:
- Development and utilization of the Quascade graphical workflow design system.
- Implementation of comparative phyloinformatics workflows in a distributed computing setting.
- Phylogenetic analysis of neuraminidase genes from H5N1 isolates and influenza viruses.
Main Results:
- Quascade enables the design and execution of complex, distributed workflows for large-scale phyloinformatics.
- Analysis of H5N1 neuraminidase demonstrates geographical clustering in phylogenetic trees.
- Identified the significance of glycan sites in the molecular evolution of H5N1.
Conclusions:
- Workflow systems like Quascade offer a biologist-friendly approach to high-performance computing for complex data analysis.
- Quascade effectively deploys distributed and parallelized phylogenetic algorithms.
- H5N1 neuraminidase datasets show spatial clustering based on geography, not temporal or host factors.
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