Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Introduction to Algorithms
A Multiple Alignment Algorithm for Metabolic Pathway Analysis Using Enzyme Hierarchy
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Top-k subgraph matching query in a large graph
Proceedings of the ACM first Ph.D. workshop in CIKM
An Introduction to Metabolic Networks and Their Structural Analysis
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Assessing the exceptionality of coloured motifs in networks
EURASIP Journal on Bioinformatics and Systems Biology - Special issue on network structure and biological function: Reconstruction, modelling, and statistical approaches
Topology-Free Querying of Protein Interaction Networks
RECOMB 2'09 Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology
Maximum Motif Problem in Vertex-Colored Graphs
CPM '09 Proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching
Evaluating the quality of clustering algorithms using cluster path lengths
ICDM'10 Proceedings of the 10th industrial conference on Advances in data mining: applications and theoretical aspects
Finding and counting vertex-colored subtrees
MFCS'10 Proceedings of the 35th international conference on Mathematical foundations of computer science
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
Upper and lower bounds for finding connected motifs in vertex-colored graphs
Journal of Computer and System Sciences
Finding approximate and constrained motifs in graphs
CPM'11 Proceedings of the 22nd annual conference on Combinatorial pattern matching
Twin-Cover: beyond vertex cover in parameterized algorithmics
IPEC'11 Proceedings of the 6th international conference on Parameterized and Exact Computation
Constrained multilinear detection for faster functional motif discovery
Information Processing Letters
Sharp tractability borderlines for finding connected motifs in vertex-colored graphs
ICALP'07 Proceedings of the 34th international conference on Automata, Languages and Programming
Density index and proximity search in large graphs
Proceedings of the 21st ACM international conference on Information and knowledge management
Domain specific vs generic network visualization: an evaluation with metabolic networks
AUIC '11 Proceedings of the Twelfth Australasian User Interface Conference - Volume 117
Finding approximate and constrained motifs in graphs
Theoretical Computer Science
RANGI: A Fast List-Colored Graph Motif Finding Algorithm
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
G-Tries: a data structure for storing and finding subgraphs
Data Mining and Knowledge Discovery
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The classic view of metabolism as a collection of metabolic pathways is being questioned with the currently available possibility of studying whole networks. Novel ways of decomposing the network into modules and motifs that could be considered as the building blocks of a network are being suggested. In this work, we introduce a new definition of motif in the context of metabolic networks. Unlike in previous works on (other) biochemical networks, this definition is not based only on topological features. We propose instead to use an alternative definition based on the functional nature of the components that form the motif, which we call a reaction motif. After introducing a formal framework motivated by biological considerations, we present complexity results on the problem of searching for all occurrences of a reaction motif in a network and introduce an algorithm that is fast in practice in most situations. We then show an initial application to the study of pathway evolution. Finally, we give some general features of the observed number of occurrences in order to highlight some structural features of metabolic networks.