Statistical significance of quantitative PCR
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* Corresponding author: Nicolas Mermod nicolas.mermod@unil.ch
BMC Bioinformatics 2007, 8:131 doi:10.1186/1471-2105-8-131
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BioMed Central: 11 citations
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Efficiency clustering for low-density microarrays and its application to QPCR Eric F Lock, Ryan Ziemiecki, JS Marron, Dirk P Dittmer BMC Bioinformatics 2010, 11:386 (20 July 2010) |
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A rapid and inexpensive labeling method for microarray gene expression analysis Mario Ouellet, Paul D Adams, Jay D Keasling, Aindrila Mukhopadhyay BMC Biotechnology 2009, 9:97 (25 November 2009) |
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Alina Rodríguez-Mallon, Yamilet Cárdenas, Juana Lugo, Aymé Oliva, Antonio Morales, Mario Estrada Biological Procedures Online 2009, 11:79-98 (10 March 2009) |
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Robert G Rutledge, Don Stewart BMC Molecular Biology 2008, 9:96 (30 October 2008) Measurement of template quantity in real-time qPCR using standard curves is prone to error, and the novel linear regression of efficiency method that calculates the amplification efficiency at the onset of each reaction is more accurate.
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Michele Guescini, Davide Sisti, Marco BL Rocchi, Laura Stocchi, Vilberto Stocchi BMC Bioinformatics 2008, 9:326 (30 July 2008) |
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Robert G Rutledge, Don Stewart BMC Biotechnology 2008, 8:47 (8 May 2008) The LRE (linear regression of efficiency) algorithm for estimating PCR efficiency is a kinetic-based sigmoidal approach that, when coupled with optical calibration, provides data comparison without using standard curves, allowing high-capacity absolute PCR quantification.
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Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry Andrej-Nikolai Spiess, Caroline Feig, Christian Ritz BMC Bioinformatics 2008, 9:221 (29 April 2008) |
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Štefan Čikoš, Alexandra Bukovská, Juraj Koppel BMC Molecular Biology 2007, 8:113 (20 December 2007) |