Michael W. Pfaffl mostly deals with Molecular biology, Real-time polymerase chain reaction, Gene expression, Computational biology and RNA. His Molecular biology study combines topics in areas such as Reverse transcriptase, Polymerase chain reaction, Ligase chain reaction, Biological system and Reproducibility. His Real-time polymerase chain reaction study integrates concerns from other disciplines, such as Reverse transcription polymerase chain reaction, Multiple displacement amplification, Amplicon and Applications of PCR.
His studies in Gene expression integrate themes in fields like Complementary DNA and Calibration curve. His Computational biology research includes themes of Normalization, Microarray analysis techniques, microRNA, DNA sequencing and Profiling. The concepts of his RNA study are interwoven with issues in Messenger RNA and Position paper.
Internal medicine, Gene expression, Endocrinology, Molecular biology and microRNA are his primary areas of study. His research investigates the connection between Internal medicine and topics such as Immune system that intersect with problems in Lactoferrin, Tumor necrosis factor alpha and Interleukin. Michael W. Pfaffl interconnects Messenger RNA and Computational biology in the investigation of issues within Gene expression.
His Computational biology research incorporates themes from Normalization and Anabolic Agents. His Molecular biology research is multidisciplinary, relying on both Cell culture, RNA, Reverse transcriptase, Polymerase chain reaction and Real-time polymerase chain reaction. His research on microRNA also deals with topics like
Michael W. Pfaffl spends much of his time researching microRNA, Cell biology, Gene expression, Internal medicine and Extracellular vesicles. His study in microRNA is interdisciplinary in nature, drawing from both Biomarker, Cancer research and RNA-Seq. His research in the fields of Signal transduction overlaps with other disciplines such as MFGE8.
Michael W. Pfaffl focuses mostly in the field of Gene expression, narrowing it down to topics relating to Reverse transcriptase and, in certain cases, Computational biology. His Internal medicine research is multidisciplinary, incorporating perspectives in Endocrinology and Mussel. His study focuses on the intersection of Small RNA and fields such as Transcriptome with connections in the field of Molecular biology, Venous blood, Fold change, Blood drawing and Spin column-based nucleic acid purification.
Michael W. Pfaffl mainly investigates microRNA, Cell biology, Extracellular vesicles, Reverse transcriptase and Cancer research. His microRNA research incorporates elements of Transcriptome and Programmed cell death. Transcriptome is the subject of his research, which falls under Gene expression.
His work on Cell to cell communication as part of general Cell biology research is often related to Basic research, thus linking different fields of science. His Reverse transcriptase study integrates concerns from other disciplines, such as Contamination, Genome and Computational biology. The Cancer research study combines topics in areas such as Proteome, Peripheral blood mononuclear cell, Apoptosis and Whole blood.
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A new mathematical model for relative quantification in real-time RT-PCR.
Michael W. Pfaffl.
Nucleic Acids Research (2001)
The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments
Stephen A. Bustin;Vladimir Benes;Jeremy A. Garson;Jan Hellemans.
Clinical Chemistry (2009)
Relative expression software tool (REST©) for group-wise comparison and statistical analysis of relative expression results in real-time PCR
Michael W. Pfaffl;Graham W. Horgan;Leo Dempfle.
Nucleic Acids Research (2002)
Minimal information for studies of extracellular vesicles 2018 (MISEV2018) : a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines
Clotilde Théry;Kenneth W. Witwer;Elena Aikawa;Maria Jose Alcaraz.
Journal of extracellular vesicles (2018)
Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper--Excel-based tool using pair-wise correlations.
Michael W. Pfaffl;Ales Tichopad;Christian Prgomet;Tanja P. Neuvians.
Biotechnology Letters (2004)
Quantitative real-time RT-PCR – a perspective
S A Bustin;V Benes;T Nolan;M W Pfaffl.
Journal of Molecular Endocrinology (2005)
RNA integrity and the effect on the real-time qRT-PCR performance
Simone Fleige;Michael W. Pfaffl.
Molecular Aspects of Medicine (2006)
The Digital MIQE Guidelines: Minimum Information for Publication of Quantitative Digital PCR Experiments
Jim F. Huggett;Carole A. Foy;Vladimir Benes;Kerry Emslie.
Clinical Chemistry (2013)
EV-TRACK: transparent reporting and centralizing knowledge in extracellular vesicle research
Jan Van Deun;Pieter Mestdagh;Patrizia Agostinis;Özden Akay.
Nature Methods (2017)
Comparison of relative mRNA quantification models and the impact of RNA integrity in quantitative real-time RT-PCR.
Simone Fleige;Vanessa Walf;Silvia Huch;Christian Prgomet.
Biotechnology Letters (2006)
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