  Boolean Networks (BNs) are established models to qualitatively describe
biological systems. The analysis of BNs might be infeasible for medium to large
BNs due to the state-space explosion problem. We propose a novel reduction
technique called \emph{Backward Boolean Equivalence} (BBE), which preserves
some properties of interest of BNs. In particular, reduced BNs provide a
compact representation by grouping variables that, if initialized equally, are
always updated equally. The resulting reduced state space is a subset of the
original one, restricted to identical initialization of grouped variables. The
corresponding trajectories of the original BN can be exactly restored. We show
the effectiveness of BBE by performing a large-scale validation on the whole
GINsim BN repository. In selected cases, we show how our method enables
analyses that would be otherwise intractable. Our method complements, and can
be combined with, other reduction methods found in the literature.
