Similarity of currently circulating H1N1 virus with the 2009 pandemic clone: Viability of an imminent pandemic

Banerjee, Rachana; Roy, Ayan; Das, Santasabuj; Basak, Surajit

doi:10.1016/j.meegid.2015.02.023

Cited by 5 publications

(2 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Chang et al studied the vaccine for influenza, so as to achieve the effect of prevention of influenza [ 4 ]. Banerjee et al made full comparisons for the structural features of all H1N1 HA gene sequences and the composition of global amino acid to make it possible to depict the developing trend of influenza A [ 5 ]. He et al also made in-depth studies to identify HA protein epitopes of avian influenza virus [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Forecasting influenza A pandemic outbreak using protein dynamical network biomarkers

et al. 2017

View full text Add to dashboard Cite

BackgroundInfluenza A virus is prone to mutation and susceptible to human beings and spread in the crowds when affected by the external environment or other factors. It is very necessary to forecast influenza A pandemic outbreak.MethodsThis paper studies the different states of influenza A in the method of dynamical network biomarkers. Through establishing protein dynamical network biomarkers of influenza A virus protein, a composite index is ultimately obtained to forecast influenza A pandemic outbreak.ResultsThe composite index varies along with the state of pandemic influenza virus from a relatively steady state to critical state before outbreak and then to the outbreak state. When the composite index continuous decreases for 2 years and increases of more than o.1 suddenly, it means the next year is normally in the outbreak state. Therefore, we can predict and identify whether a certain year is in the critical state before influenza A outbreak or outbreak state by observing the variation of index value. Meanwhile, through data analysis for different countries influenza A pandemic outbreak in different countries can also be forecasted.ConclusionsThis indicates the composite index can provide significant warning information to detect the stage of influenza A, which will be significantly meaningful for the warning and prevention of influenza A pandemic.

show abstract

Section: Introductionmentioning

confidence: 99%

Forecasting influenza A pandemic outbreak using protein dynamical network biomarkers

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Chang et al (2009) studied the vaccine for influenza, so as to achieve the effect of prevention of influenza. Banerjee et al (2015) made full comparisons for the structural features of all H1N1 HA gene sequences and the composition of global amino acid to make it possible to depict the developing trend of influenza A. He et al (2014) also made indepth studies to identify HA protein epitopes of avian influenza virus.…”

Section: Introductionmentioning

confidence: 99%

Detecting early-warning signals for influenza A pandemic based on protein dynamical network biomarkers

Gao

Wang

Ding

2017

Saudi Journal of Biological Sciences

View full text Add to dashboard Cite

The outbreak of influenza A comes from a relatively stable state is a critical phenomenon on epidemic. In this paper, influenza A varying from different states is studied in the method of dynamical network biomarkers (DNB). Through studying DNB of influenza A virus protein, we can detect the warning signals of outbreak for influenza A and obtain a composite index. The composite index varies along with the state of pandemic influenza, which gives a clue showing the turn point of outbreak. The low value (<1) steady state of the composite index means influenza A is normally in the relatively steady stage. Meanwhile, if the composite index of a certain year increases by more than 0.8 relative to the previous year and it is less than 1 and it increases sharply and reaches a peak being larger than 1 in next year, it means the year is normal in the critical state before outbreak and the next year is normally in the outbreak state. Therefore, we can predict the outbreak of influenza A and identify the critical state before influenza A outbreak or outbreak state by observing the variation of index value.

show abstract

Novel antigenic shift in HA sequences of H1N1 viruses detected by big data analysis

Zhang

Duan

2017

Infection, Genetics and Evolution

View full text Add to dashboard Cite

Similarity of currently circulating H1N1 virus with the 2009 pandemic clone: Viability of an imminent pandemic

Cited by 5 publications

References 31 publications

Forecasting influenza A pandemic outbreak using protein dynamical network biomarkers

Forecasting influenza A pandemic outbreak using protein dynamical network biomarkers

Detecting early-warning signals for influenza A pandemic based on protein dynamical network biomarkers

Novel antigenic shift in HA sequences of H1N1 viruses detected by big data analysis

Contact Info

Product

Resources

About