In the network querying problem, one is given a protein complex or pathway of species
and a protein–protein interaction network of species
; the goal is to identify subnetworks of
that are similar to the query. Existing approaches mostly depend on knowledge of the interaction topology of the query in the network of species
; however, in practice, this topology is often not known. To combat this problem, we develop a topology-free querying algorithm, which we call
. Given a query, represented as a set of proteins,
seeks a matching set of proteins that are sequence-similar to the query proteins and span a connected region of the network, while allowing both insertions and deletions. The algorithm uses alternatively dynamic programming and integer linear programming for the search task. We test
with queries from yeast, fly, and human, where we compare it to the QNet topology-based approach, and with queries from less studied species, where only topology-free algorithms apply.
detects many more matches than QNet, while in both cases giving results that are highly functionally coherent.