Here we discuss “hidden variables”,
which are typically
introduced during an experiment as a consequence of the application
of two independent variables together to create a stimulus. With increased
sophistication in modern chemical biology tools and related precision
interrogation techniques, hidden variables have become integral to
many chemical biologists’ routine experiments. For instance,
they can appear in the use of light-activatable chemical probes (e.g.,
μMap, T-REX), or stimulus-induced enzyme activation (e.g., APEX).
Unfortunately, control experiments assess only how independent variables
affect measured outcomes and not the multiple differences between
the two independent variables and the twain. We outline ways to account
for potential hidden variables in experimental design and data interpretation
as a means to aid developers of new methods, particularly those involving
light-driven techniques, chemical activation, or biorthogonal chemistries,
to better incorporate well-controlled procedures.