  Information theory is gaining popularity as a tool to characterize
performance of biological systems. However, information is commonly quantified
without reference to whether or how a system could extract and use it; as a
result, information-theoretic quantities are easily misinterpreted. Here we
take the example of pattern-forming developmental systems which are commonly
structured as cascades of sequential gene expression steps. Such a multi-tiered
structure appears to constitute sub-optimal use of the positional information
provided by the input morphogen because noise is added at each tier. However,
the conventional theory fails to distinguish between the total information in a
morphogen and information that can be usefully extracted and interpreted by
downstream elements. We demonstrate that quantifying the information that is
_accessible_ to the system naturally explains the prevalence of multi-tiered
network architectures as a consequence of the noise inherent to the control of
gene expression. We support our argument with empirical observations from
patterning along the major body axis of the fruit fly embryo. Our results
exhibit the limitations of the standard information-theoretic characterization
of biological signaling and illustrate how they can be resolved.
