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New searchable influenza gene database

Published on April 26, 2007 at 5:30 AM · No Comments

A Medical College of Wisconsin and Children's Research Institute team in Milwaukee has created a free, searchable genetic database that will significantly improve diagnostic testing and genetic tracking of human and animal influenza viruses.

The site, which is automatically updated weekly, will also facilitate rapid response as new virus strains emerge to cause either annual epidemics or the next pandemic.

In a striking example of translational, or bench-to-bedside, research the multidisciplinary team has created a searchable database, containing all accessible genetic sequences of influenza A, B, and C and integrated them into the website, www.IPDR.mcw.edu. The website was presented at two recent meetings: Seasonal & Pandemic Influenza, 2007 in Arlington, VA, and IX International Symposium on Respiratory viral infections in Hong Kong.

With the widespread availability of rapid genetic testing for influenza in clinics and laboratories, considerable resources are spent on bioinformatics annually, by many researchers and funding agencies worldwide , trying to improve influenza diagnostics, according to presenting author Kelly Henrickson, M.D., professor of pediatrics and microbiology.

“Since the 1997 Hong Kong bird flu outbreak, the focus of the world and its scientific community has intensified on all aspects of influenza,” he says. “As a result, there has been a significant increase in the amount of genomic data for influenza, which is now greater than 46,000 genetic sequences and growing by hundreds monthly.”

Constantly updated to keep pace with emergence of new virus strains, this tool will also reduce the enormous resources being expended worldwide on duplicate efforts. The site's simple, pop-up query screen, allows all 46,000+ sequences in its database to be searched, or probed, with a set of criteria including: gene segment, year, species, geographic location, and subtype. The unique feature of this website is that after quickly aligning the genetic sequences, it displays the consensus sequence with the percentage of match, mismatch and gap at each position for rapid identification of the strain being tested.

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