Journal of the ACM (JACM)
Introduction to Algorithms
Alignment of metabolic pathways
Bioinformatics
Motif Search in Graphs: Application to Metabolic Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Fourier meets möbius: fast subset convolution
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Parameterized Algorithms and Hardness Results for Some Graph Motif Problems
CPM '08 Proceedings of the 19th annual symposium on Combinatorial Pattern Matching
Fast and accurate alignment of multiple protein networks
RECOMB'08 Proceedings of the 12th annual international conference on Research in computational molecular biology
Sharp tractability borderlines for finding connected motifs in vertex-colored graphs
ICALP'07 Proceedings of the 34th international conference on Automata, Languages and Programming
Maximum Motif Problem in Vertex-Colored Graphs
CPM '09 Proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching
Finding and counting vertex-colored subtrees
MFCS'10 Proceedings of the 35th international conference on Mathematical foundations of computer science
Heuristic algorithms in computational molecular biology
Journal of Computer and System Sciences
Querying Graphs in Protein-Protein Interactions Networks Using Feedback Vertex Set
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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
RANGI: A Fast List-Colored Graph Motif Finding Algorithm
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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In the network querying problem, one is given a protein complex or pathway of species A and a protein---protein interaction network of species B ; the goal is to identify subnetworks of B that are similar to the query. Existing approaches mostly depend on knowledge of the interaction topology of the query in the network of species A ; however, in practice, this topology is often not known. To combat this problem, we develop a topology-free querying algorithm, which we call Torque . Given a query, represented as a set of proteins, Torque 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 Torque 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. Torque detects many more matches than QNet, while in both cases giving results that are highly functionally coherent.