Inference of Sequence Homology by BLAST visualization of Influenza Genome set

Influenza viruses are known to cause annual epidemics and occasional pandemics which have severely impacted on public safety and economy. Understanding the origins of the novel strains of influenza can better predict the lethality of the new strain and prepare appropriate countermeasures to reduce the economic impact of potential pandemics. Researchers are usually overwhelmed with too much data. This paper aims to ease preliminary investigation task of data exploration, enabling domain expert to gain a better understand its specific characteristics. We developed a webbased application to explore the genomic sequence homology that improves upon current BLAST visualizations by summarizing additional supplementary data from BLAST hits into insightful charts. The application requires the influenza genome dataset as the input. The visualized results would provide users comprehensive knowledge to make inferences about the sequence homology of the queried influenza genome set, and hopefully to inspire some insightful hypotheses. The web application is publicly available at http://blastviz.scse.ntu.edu.sg.