A Multiple Alignment Algorithm for Metabolic Pathway Analysis Using Enzyme Hierarchy
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
Approximation algorithms for maximum dispersion
Operations Research Letters
Towards graph containment search and indexing
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
A parallel edge-betweenness clustering tool for Protein-Protein Interaction networks
International Journal of Data Mining and Bioinformatics
GOSAP: Gene Ontology-Based Semantic Alignment of Biological Pathways
International Journal of Bioinformatics Research and Applications
Dividing Protein Interaction Networks by Growing Orthologous Articulations
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
Finding occurrences of protein complexes in protein-protein interaction graphs
Journal of Discrete Algorithms
GADDI: distance index based subgraph matching in biological networks
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Maximum Motif Problem in Vertex-Colored Graphs
CPM '09 Proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching
Pairwise global alignment of protein interaction networks by matching neighborhood topology
RECOMB'07 Proceedings of the 11th annual international conference on Research in computational molecular biology
Divide, align and full-search for discovering conserved protein complexes
EvoBIO'08 Proceedings of the 6th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
Protein-to-protein interactions: Technologies, databases, and algorithms
ACM Computing Surveys (CSUR)
Dividing protein interaction networks for modular network comparative analysis
Pattern Recognition Letters
SAPPER: subgraph indexing and approximate matching in large graphs
Proceedings of the VLDB Endowment
Complexity issues in vertex-colored graph pattern matching
Journal of Discrete Algorithms
Finding approximate and constrained motifs in graphs
CPM'11 Proceedings of the 22nd annual conference on Combinatorial pattern matching
Identification of conserved protein complexes by module alignment
International Journal of Data Mining and Bioinformatics
A novel framework for large scale metabolic network alignments by compression
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Assessing significance of connectivity and conservation in protein interaction networks
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
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With ever increasing amount of available data on protein-protein interaction (PPI) networks and research revealing that these networks evolve at a modular level, discovery of conserved patterns in these networks becomes an important problem. Recent algorithms on aligning PPI networks target simplified structures such as conserved pathways to render these problems computationally tractable. However, since conserved structures that are parts of functional modules and protein complexes generally correspond to dense subnets of the network, algorithms that are able to extract conserved patterns in terms of general graphs are necessary. With this motivation, we focus here on discovering protein sets that induce subnets that are highly conserved in the interactome of a pair of species. For this purpose, we develop a framework that formally defines the pairwise local alignment problem for PPI networks, models the problem as a graph optimization problem, and presents fast algorithms for this problem. In order to capture the underlying biological processes correctly, we base our framework on duplication/divergence models that focus on understanding the evolution of PPI networks. Experimental results from an implementation of the proposed framework show that our algorithm is able to discover conserved interaction patterns very effectively (in terms of accuracies and computational cost). While we focus on pairwise local alignment of PPI networks in this paper, the proposed algorithm can be easily adapted to finding matches for a subnet query in a database of PPI networks.