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Enzyme Immunoassays for Anti-Hepatitis C Virus Antibodies Improved Specificity and Analytical Sensitivity by Combination of Three Different Recombinant Viral Proteins in Second Generation Tests

  • W. Prohaska , E. Schroeter , Petra Kaars-Wiele and K. Kleesiek
Published/Copyright: October 21, 2009
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Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Volume 30 Issue 7

Published Online: 2009-10-21
Published in Print: 1992

Walter de Gruyter

Articles in the same Issue

  1. Titelei
  2. Sonstiges
  3. Beeinflussung membrangebundener Enzymaktivitäten durch Veränderung der Membranlipidzusammensetzung
  4. Isoelectric Focussing of Human Thyroxine Binding Globulin (Thyropexin) and Human Prealbumin (Transthyretin)
  5. A New Automated Method for Phenotyping Arylesterase (EC 3.1.1.2) Based Upon Inhibition of Enzymatic Hydrolysis of 4-Nitrophenyl Acetate by Phenyl Acetate
  6. Enzyme Immunoassays for Anti-Hepatitis C Virus Antibodies Improved Specificity and Analytical Sensitivity by Combination of Three Different Recombinant Viral Proteins in Second Generation Tests
  7. Robust Bivariate Errors-in-Variables Regression and Outlier Detection
  8. Rationale for Using Multiple Regression Analysis with Complex Interferences
  9. SHORT COMMUNICATION
  10. TECHNICAL NOTE
  11. TECHNICAL REPORT
  12. Award
https://doi.org/10.1515/cclm.1992.30.7.397

Articles in the same Issue

  1. Titelei
  2. Sonstiges
  3. Beeinflussung membrangebundener Enzymaktivitäten durch Veränderung der Membranlipidzusammensetzung
  4. Isoelectric Focussing of Human Thyroxine Binding Globulin (Thyropexin) and Human Prealbumin (Transthyretin)
  5. A New Automated Method for Phenotyping Arylesterase (EC 3.1.1.2) Based Upon Inhibition of Enzymatic Hydrolysis of 4-Nitrophenyl Acetate by Phenyl Acetate
  6. Enzyme Immunoassays for Anti-Hepatitis C Virus Antibodies Improved Specificity and Analytical Sensitivity by Combination of Three Different Recombinant Viral Proteins in Second Generation Tests
  7. Robust Bivariate Errors-in-Variables Regression and Outlier Detection
  8. Rationale for Using Multiple Regression Analysis with Complex Interferences
  9. SHORT COMMUNICATION
  10. TECHNICAL NOTE
  11. TECHNICAL REPORT
  12. Award
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