Detail publikace

Paramagnetic particles coupled with an automated flow injection analysis as a tool for influenza viral protein detection

Originální název

Paramagnetic particles coupled with an automated flow injection analysis as a tool for influenza viral protein detection

Anglický název

Paramagnetic particles coupled with an automated flow injection analysis as a tool for influenza viral protein detection

Jazyk

en

Originální abstrakt

Currently, the influenza virus infectsmillions of individuals every year. Since the influenza virus represents one of the greatest threats, it is necessary to develop a diagnostic technique that can quickly, inexpensively, and accurately detect the virus to effectively treat and control seasonal and pandemic strains. This study presents an alternative to current detectionmethods

Anglický abstrakt

Currently, the influenza virus infectsmillions of individuals every year. Since the influenza virus represents one of the greatest threats, it is necessary to develop a diagnostic technique that can quickly, inexpensively, and accurately detect the virus to effectively treat and control seasonal and pandemic strains. This study presents an alternative to current detectionmethods

BibTex


@article{BUT95482,
  author="Ludmila {Krejčová} and Dana {Fialová} and Markéta {Vaculovičová} and Pavel {Kopel} and David {Hynek} and Soňa {Křížková} and Jaromír {Hubálek} and Vojtěch {Adam} and René {Kizek}",
  title="Paramagnetic particles coupled with an automated flow injection analysis as a tool for influenza viral protein detection",
  annote="Currently, the influenza virus infectsmillions of individuals every year. Since the influenza
virus represents one of the greatest threats, it is necessary to develop a diagnostic technique
that can quickly, inexpensively, and accurately detect the virus to effectively treat
and control seasonal and pandemic strains. This study presents an alternative to current detectionmethods",
  chapter="95482",
  doi="10.1002/elps.201200304",
  number="21",
  volume="33",
  year="2012",
  month="november",
  pages="3195--3204",
  type="journal article in Web of Science"
}