Algorithmic Aspects of Heterogeneous Biological Networks Comparison
Biological networks are commonly used to model molecular activity within the cell. Recent experimental studies have shown that the detection of conserved subnetworks across several networks, coming from different organisms, may allow the discovery of disease pathways and prediction of protein functions. There already exist automatic methods that allow to search for conserved subnetworks using networks alignment; unfortunately, these methods are limited to networks of same type, thus having the same graph representation. Towards overcoming this limitation, a unified framework for pairwise comparison and analysis of networks with different graph representations (in particular, a directed acyclic graph D and an undirected graph G over the same set of vertices) is presented in . We consider here a related problem called k -DAGCC: given a directed graph D and an undirected graph G on the same set V of vertices, and an integer k, does there exist sets of vertices V 1, V 2, …V k′, k′ ≤ k such that, for each 1 ≤ i ≤ k′, (i) D[V i ] is a DAG and (ii) G[V i ] is connected ? Two variants of k -DAGCC are of interest: (a) the V i s must form a partition of V, or (b) the V i s must form a cover of V. We study the computational complexity of both variants of k -DAGCC and, depending on the constraints imposed on the input, provide several polynomial-time algorithms, hardness and inapproximability results.
KeywordsDirected Graph Metabolic Network Directed Acyclic Graph Undirected Graph Protein Interaction Network
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