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Assumptions of biological measurements: important considerations when evaluating western blot data
  • Maxwell DeNies,
  • Allen Liu,
  • Santiago Schnell
Maxwell DeNies
University of Michigan Medical School

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Allen Liu
University of Michigan College of Engineering
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Santiago Schnell
University of Michigan Medical School
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As technological and analytical innovations rapidly advance our ability to reveal increasingly complex biological processes, the importance of understanding the assumptions behind biological measurements and sources of uncertainty are essential for data interpretation. This is particularly important in fields such as cell signaling, as due to its importance for both homeostatic and pathogenic biological processes, a quantitative understanding of the basic mechanisms of these transient events is fundamental to drug development. While developed decades ago, western blotting remains an indispensible research tool to probe cell signaling, protein expression, and protein-protein interactions. While improvements in statistical and methodology reporting have improved data quality, understanding the basic experimental assumptions and visual inspection of western blots provides additional information that is useful when evaluating experimental conclusions. Using agonist-induced receptor post-translational modification as an example we highlight the assumptions of western blotting and showcase how clues from raw western blots can hint at experimental variability that is not captured by statistics and methods that influences quantification. The purpose of this article is not to serve as a detailed review of the technical nuances and caveats of western blotting. Instead using an example we illustrate how experimental assumptions, design, and data normalization can be identified in raw data and influence data interpretation.