The igraph software package for complex network research. igraph is a free software package for creating and manipulating undirected and directed graphs. It includes implementations for classic graph theory problems like minimum spanning trees and network flow, and also implements algorithms for some recent network analysis methods, like community structure search. The efficient implementation of igraph allows it to handle graphs with millions of vertices and edges. The rule of thumb is that if your graph fits into the physical memory then igraph can handle it.

References in zbMATH (referenced in 126 articles )

Showing results 61 to 80 of 126.
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  1. Santtu Tikka and Juha Karvanen: Identifying Causal Effects with the R Package causaleffect (2017) not zbMATH
  2. Sharma, Rohan; Adhikari, Bibhas; Mishra, Abhishek: Structural and spectral properties of corona graphs (2017)
  3. Thong Pham, Paul Sheridan, Hidetoshi Shimodaira: PAFit: An R Package for Modeling and Estimating Preferential Attachment and Node Fitness in Temporal Complex Networks (2017) arXiv
  4. Bar-Hen, Avner; Poggi, Jean-Michel: Influence measures and stability for graphical models (2016)
  5. Clemente, Gian Paolo; Cornaro, Alessandra: Bounding the (HL)-index of a graph: a majorization approach (2016)
  6. Ferreira, Leonardo N.; Zhao, Liang: Time series clustering via community detection in networks (2016)
  7. Ioanna Manolopoulou, Axel Hille: BPEC: An R Package for Bayesian Phylogeographic and Ecological Clustering (2016) arXiv
  8. Malmros, J.; Liljeros, F.; Britton, T.: Respondent-driven sampling and an unusual epidemic (2016)
  9. Matthew Friedlander: The Bayesian analysis of contingency table data using the bayesloglin R package (2016) arXiv
  10. Michael Scholz: R Package clickstream: Analyzing Clickstream Data with Markov Chains (2016) not zbMATH
  11. Miecznikowski, Jeffrey C.; Gaile, Daniel P.; Chen, Xiwei; Tritchler, David L.: Identification of consistent functional genetic modules (2016)
  12. Noureddine, Mohammad A.; Fawaz, Ahmed; Sanders, William H.; Başar, Tamer: A game-theoretic approach to respond to attacker lateral movement (2016)
  13. Patrick Roocks: Computing Pareto Frontiers and Database Preferences with the rPref Package (2016) not zbMATH
  14. Riondato, Matteo; Kornaropoulos, Evgenios M.: Fast approximation of betweenness centrality through sampling (2016)
  15. Weishaupt, Holger; Johansson, Patrik; Engström, Christopher; Nelander, Sven; Silvestrov, Sergei; Swartling, Fredrik J.: Graph centrality based prediction of cancer genes (2016)
  16. Barbillon, Pierre; Thomas, Mathieu; Goldringer, Isabelle; Hospital, Frédéric; Robin, Stéphane: Network impact on persistence in a finite population dynamic diffusion model: application to an emergent seed exchange network (2015)
  17. Dahm, Nicholas; Bunke, Horst; Caelli, Terry; Gao, Yongsheng: Efficient subgraph matching using topological node feature constraints (2015)
  18. Donges, Jonathan F.; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V.; Marwan, Norbert; Dijkstra, Henk A.; Kurths, Jürgen: Unified functional network and nonlinear time series analysis for complex systems science: the pyunicorn package (2015)
  19. Jonathan F. Donges, Jobst Heitzig, Boyan Beronov, Marc Wiedermann, Jakob Runge, Qing Yi Feng, Liubov Tupikina, Veronika Stolbova, Reik V. Donner, Norbert Marwan, Henk A. Dijkstra, J. Kurths: Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package (2015) arXiv
  20. Ma, Tinghuai; Zhang, Yuliang; Cao, Jie; Shen, Jian; Tang, Meili; Tian, Yuan; Al-Dhelaan, Abdullah; Al-Rodhaan, Mznah: KDVEM: a (k)-degree anonymity with vertex and edge modification algorithm (2015)