Network motif detection is the search for statistically overrepresented subgraphs present in a larger target network. They are thought to represent key structure and control mechanisms. Although the problem is exponential in nature, several…

Network motif detection is the search for statistically overrepresented subgraphs present in a larger target network. They are thought to represent key structure and control mechanisms. Although the problem is exponential in nature, several algorithms and tools have been developed for efficiently detecting network motifs

A software tool that uses the g-trie data structure to count occurrences of…

A software tool that uses the g-trie data structure to count occurrences of subgraphs on larger graphs, determining if they are network motifs. To compile you need a C++ compiler (use GCC if…

Enumerates all instances of a motif in a graph, making optimal use of the…

Enumerates all instances of a motif in a graph, making optimal use of the motif’s symmetries to make the search more efficient. The ISMAGS algorithm is able to enumerate all instances of a motif…

Enables generation of hypotheses on the evolution of metabolic pathways. MOTUS…

Enables generation of hypotheses on the evolution of metabolic pathways. MOTUS also analyzes some global features of the whole network. It uses the reaction graph as model for the metabolic network.…

Identify diﬀerential sub-networks as differential communities in a de-noised…

Identify diﬀerential sub-networks as differential communities in a de-noised version of the different topological (DT) graph. DCD can (i) iteratively re-order the nodes of the DT graph to determine…

Provides options for network design. A user defines the number of network…

Provides options for network design. A user defines the number of network components, order and sign of regulatory links between the components. NetExplore allows plotting and visualization of the…

A randomization algorithm that for the first time provides a practical network…

A randomization algorithm that for the first time provides a practical network motif discovery method for large multi-layer networks, for example those that include transcription factors, microRNAs,…

A tool for fast network motif detection. FANMOD relies on recently developed…

A tool for fast network motif detection. FANMOD relies on recently developed algorithms to improve the efficiency of network motif detection by some orders of magnitude over existing tools. This…

Allows estimation of subgraph concentrations and detection of network motifs at…

Allows estimation of subgraph concentrations and detection of network motifs at a runtime that is asymptotically independent of the network size. mfinder is based on random sampling of subgraphs.…

A network motif detection package. NetMODE also (a) includes a method for…

A network motif detection package. NetMODE also (a) includes a method for generating comparison graphs uniformly at random, (b) can interface with external packages (e.g. R), and (c) can utilize…

A free software tool to detect network motifs os size 3, 4 and 5. It is…

A free software tool to detect network motifs os size 3, 4 and 5. It is implemented in Java. acc-MOTIF is based in a recent combinatorial approach to accelerate motif detection.

An algorithm for finding k-size network motifs with less memory and CPU time in…

An algorithm for finding k-size network motifs with less memory and CPU time in comparison to other existing algorithms. Kavosh is based on counting all k-size sub-graphs of a given graph (directed…

A tool for the exploration of motifs in network. MAVisto provides a flexible…

A tool for the exploration of motifs in network. MAVisto provides a flexible motif search algorithm and different views for the analysis and visualisation of network motifs. It is written in Java and…

Provides a fast motif detection algorithm which has a Quaternary Tree data…

Provides a fast motif detection algorithm which has a Quaternary Tree data structure in the heart. QuateXelero is especially fastest in constructing the central data structure of the algorithm from…

An algorithm that incorporates techniques such as a pattern growth approach for…

An algorithm that incorporates techniques such as a pattern growth approach for extracting larger motifs efficiently. While most of the algorithms rely on induced subgraphs as motifs of the networks,…