  We consider a simplified model for gene regulation, where gene expression is
regulated by transcription factors (TFs), which are single proteins or protein
complexes. Proteins are in turn synthesised from expressed genes, creating a
feedback loop of regulation. This leads to a directed bipartite network in
which a link from a gene to a TF exists if the gene codes for a protein
contributing to the TF, and a link from a TF to a gene exists if the TF
regulates the expression of the gene. Both genes and TFs are modelled as binary
variables, which indicate, respectively, whether a gene is expressed or not,
and a TF is synthesised or not. We consider the scenario where for a TF to be
synthesised, all of its contributing genes must be expressed. This results in
an ``AND'' gate logic for the dynamics of TFs. By adapting percolation theory
to directed bipartite graphs, evolving according to the AND logic dynamics, we
are able to determine the necessary conditions, in the network parameter space,
under which bipartite networks can support a multiplicity of stable gene
expression patterns, under noisy conditions, as required in stable cell types.
  In particular, the analysis reveals the possibility of a bi-stability region,
where the extensive percolating cluster is or is not resilient to
perturbations. This is remarkably different from the transition observed in
standard percolation theory. Finally, we consider perturbations involving
single node removal that mimic gene knockout experiments. Results reveal the
strong dependence of the gene knockout cascade on the logic implemented in the
underlying network dynamics, highlighting in particular that avalanche sizes
cannot be easily related to gene-gene interaction networks.
