  This paper studies the mathematical properties of collectively canalizing
Boolean functions, a class of functions that has arisen from applications in
systems biology. Boolean networks are an increasingly popular modeling
framework for regulatory networks, and the class of functions studied here
captures a key feature of biological network dynamics, namely that a subset of
one or more variables, under certain conditions, can dominate the value of a
Boolean function, to the exclusion of all others. These functions have rich
mathematical properties to be explored. The paper shows how the number and type
of such sets influence a function's behavior and define a new measure for the
canalizing strength of any Boolean function. We further connect the concept of
collective canalization with the well-studied concept of the average
sensitivity of a Boolean function. The relationship between Boolean functions
and the dynamics of the networks they form is important in a wide range of
applications beyond biology, such as computer science, and has been studied
with statistical and simulation-based methods. But the rich relationship
between structure and dynamics remains largely unexplored, and this paper is
intended as a contribution to its mathematical foundation.
