FANMOD: a tool for fast network motif detection. Motifs are small connected subnetworks that a network displays in significantly higher frequencies than would be expected for a random network. They have recently gathered much attention as a concept to uncover structural design principles of complex biological networks. FANMOD is a tool for fast network motif detection; it relies on recently developed algorithms to improve the efficiency of network motif detection by some orders of magnitude over existing tools. This facilitates the detection of larger motifs in bigger networks than previously possible. Additional benefits of FANMOD are the ability to analyze colored networks, a graphical user interface and the ability to export results to a variety of machine- and human-readable file formats including comma-separated values and HTML.

References in zbMATH (referenced in 13 articles )

Showing results 1 to 13 of 13.
Sorted by year (citations)

  1. Rubert, Diego P.; Araujo, Eloi; Stefanes, Marco A.; Stoye, Jens; Martinez, Fábio V.: Searching and inferring colorful topological motifs in vertex-colored graphs (2020)
  2. Garavaglia, Alessandro; Stegehuis, Clara: Subgraphs in preferential attachment models (2019)
  3. Nie, Chun-Xiao: Applying correlation dimension to the analysis of the evolution of network structure (2019)
  4. Merhej, Elie; Schockaert, Steven; De Cock, Martine: Repairing inconsistent answer set programs using rules of thumb: a gene regulatory networks case study (2017)
  5. Navlakha, Saket: Learning the structural vocabulary of a network (2017)
  6. Topirceanu, Alexandru; Udrescu, Mihai: Statistical fidelity: a tool to quantify the similarity between multi-variable entities with application in complex networks (2017)
  7. Erciyes, K.: Distributed and sequential algorithms for bioinformatics (2015)
  8. Shahrivari, Saeed; Jalili, Saeed: Distributed discovery of frequent subgraphs of a network using MapReduce (2015)
  9. Panigrahi, Priya P.; Singh, Tiratha Raj: Computational studies on Alzheimer’s disease associated pathways and regulatory patterns using microarray gene expression and network data: revealed association with aging and other diseases (2013)
  10. Birmelé, Etienne: Detecting local network motifs (2012)
  11. Ribeiro, Pedro; Silva, Fernando; Lopes, Luís: Parallel discovery of network motifs (2012) ioport
  12. Malkoç, Berkin; Balcan, Duygu; Erzan, Ayşe: Information content based model for the topological properties of the gene regulatory network of \textitEscherichiacoli (2010)
  13. Wernicke, Sebastian; Rasche, Florian: Fanmod: A tool for fast network motif detection (2006) ioport