- The first week of learning Networks an introduction (by M. E. J. Newman) (http://math.sjtu.edu.cn/faculty/xiaodong/course/Networks%20An%20introduction.pdf)
- Nauty and Traces (http://pallini.di.uniroma1.it)
- Nauty and Traces user’s guide (https://users.cecs.anu.edu.au/~bdm/nauty/nug26.pdf)
- The method that it uses to search for motifs is the Monte Carlo sampling technique. Here is the link to the package (https://github.com/dshemetov/GraphletLift)
- The link to the paper relates to that repository GraphletLift (https://arxiv.org/abs/1802.08736)
- The link of a package that works for counting motifs in large sparse graphs (https://github.com/nkahmed/pgd#input-file-format)
- The paper regarding Kavosh algorithm for finding motifs (https://www.academia.edu/811167/Kavosh_a_new_algorithm_for_finding_network_motifs)
- Different methods for analyzing network motifs (http://www.cs.tau.ac.il/~roded/courses/bnet-a06/lec04.pdf)
- Differentiate biological network motifs as biologically significant subgraphs and traditional network motifs as structural network motifs (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287573)
- Counting the number of motifs in a dynamic biological network (https://bmcsystbiol.biomedcentral.com/articles/10.1186/s12918-018-0533-6)
- A survey network motif search algorithms in general (https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6616521)