Predicting antigenic changes of influenza viruses using text data assimilation.

2015 Fiscal Year Final Research Report

• Project/Area Number: 25280080
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Partial Multi-year Fund
• Section: 一般
• Research Field: Intelligent informatics
• Research Institution: Hokkaido University
• Principal Investigator: Kimihito Ito 北海道大学, 人獣共通感染症リサーチセンター, 教授 (60396314)
• Co-Investigator(Renkei-kenkyūsha): TAKADA Ayato 北海道大学, 人獣共通感染症リサーチセンター, 教授 (10292062) ; IGARASHI Manabu 北海道大学, 人獣共通感染症リサーチセンター, 准教授 (10374240)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: インフルエンザ / 抗原変異予測 / データ同化 / ワクチン

Outline of Final Research Achievements

Human influenza viruses mutate from time to time, causing annual epidemics worldwide. Given the high mutation rate of the viral gene, influenza vaccine strains need to be updated every two to three years. In order to prepare an effective vaccine strain prior to each influenza season, we investigated text data assimilation methods that allow us to predict the evolution of viral amino acid sequences. As a result, we developed a mathematical model consisting of human herd immunity, the number of infections, and population of circulating vires. The model provides a mathematical basis of bioinformatics methods to prepare an effective vaccine strain prior to influenza seasons.

Free Research Field

生命情報科学