Assumptions of biological measurements: important considerations when
evaluating western blot data
- Maxwell DeNies,
- Allen Liu,
- Santiago Schnell

Abstract
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.