Earticle

초록

영어

Influenza virus undergoes continuous changes, evolving into different types every year; in fact, there are up to 198subtypes of the influenza virus. Each subtype infects a different animal species and has different levels of infectivity. The infection pattern and time of outbreak of each subtype can be analyzed to predict its infectivity. Conventional approaches involve the use of simple DNA or protein sequencing methods to evaluate the viral toxicity. However, this approach cannot explain complex biological behavior resulting from various interactions. In this study, a new mathematical model was developed to evaluate the central dogma, and the model was used to predict the pandemic, epidemic, or reassortment nature of the virus.

목차

Abstract
 1. Introduction
 2. Method
  2.1. New Mathematical Model of Biological Information Stream (BIS) for the Prediction of Pandemics and Epidemics
  2.2. Using Shannon Entropy to Analyze the Properties of DNA and Protein
  2.3. Data Collection for Protein Analysis (1918 H1N1 Influenza A virus ~ 2009 H1N1 Influenza A virus and H2N2, H3N1, H5N1)
 3. Result
  3.1. Pandemic and Epidemiology of Influenza Virus
  3.2. Biological Information Stream (BIS) of H1N1 Hemagglutinin
  3.3. Calculation of Shannon Entropy for H1N1 Protein and DNA Sequences
  3.4. A Comparison of the BIS and Shannon Entropy
 4. Discussion
 References

키워드

저자

• Se-Eun Bae [ KM Fundamental Research Division, Korea Institute of Oriental Medicine, Daejeon, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605