Spinal: scalable protein interaction network alignment, Bioinformatics, vol.29, issue.7, pp.917-924, 2013. ,
Algorithms for large, sparse network alignment problems, IEEE International Conference on Data Mining (ICDM, pp.705-710, 2009. ,
Direction-optimizing breadth-first search, Scientific Programming, vol.21, issue.3-4, pp.137-148, 2013. ,
DOI : 10.1155/2013/702694
URL : https://doi.org/10.1155/2013/702694
WebGraph Datasets: Laboratory for algorithmics, 2018. ,
Optimizing a global alignment of protein interaction networks, Bioinformatics, vol.29, issue.21, pp.2765-2773, 2013. ,
Thirty years of graph matching in pattern recognition, International journal of pattern recognition and artificial intelligence, vol.18, issue.03, pp.265-298, 2004. ,
URL : https://hal.archives-ouvertes.fr/hal-01408706
BigDND: Big dynamic network data, 2017. ,
Lagrangian relaxation applied to sparse global network alignment, IAPR International Conference on Pattern Recognition in Bioinformatics, pp.225-236, 2011. ,
DOI : 10.1007/978-3-642-24855-9_20
URL : https://link.springer.com/content/pdf/10.1007%2F978-3-642-24855-9_20.pdf
Global alignment of proteinprotein interaction networks: A survey, IEEE Transactions on Computational Biology and Bioinformatics, vol.13, issue.4, pp.689-705, 2016. ,
Quad trees a data structure for retrieval on composite keys, Acta informatica, vol.4, issue.1, pp.1-9, 1974. ,
DOI : 10.1007/bf00288933
A new graph-based method for pairwise global network alignment, BMC Bioinformatics, vol.10, issue.1, p.59, 2009. ,
Network similarity decomposition (nsd): A fast and scalable approach to network alignment, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol.24, issue.12, pp.2232-2243, 2012. ,
Big-align: Fast bipartite graph alignment, IEEE International Conference on Data Mining (ICDM), pp.389-398, 2013. ,
DOI : 10.1109/icdm.2013.152
Using local similarity measures to efficiently address approximate graph matching, Discrete Applied Mathematics, vol.164, pp.161-177, 2014. ,
DOI : 10.1016/j.dam.2012.01.019
Topological network alignment uncovers biological function and phylogeny, Journal of the Royal Society Interface, vol.7, issue.50, pp.1341-1354, 2010. ,
DOI : 10.1098/rsif.2010.0063
URL : http://rsif.royalsocietypublishing.org/content/7/50/1341.full.pdf
Isorankn: spectral methods for global alignment of multiple protein networks, Bioinformatics, vol.25, issue.12, pp.253-258, 2009. ,
A multiobjective memetic algorithm based on particle swarm optimization, IEEE Transactions on Systems, Man, and Cybernetics, vol.37, pp.42-50, 2007. ,
L-graal: Lagrangian graphlet-based network aligner, Bioinformatics, vol.31, issue.13, pp.2182-2189, 2015. ,
DOI : 10.1093/bioinformatics/btv130
URL : https://academic.oup.com/bioinformatics/article-pdf/31/13/2182/17122621/btv130.pdf
C-graal: C ommon-neighbors-based global gra ph al ignment of biological networks, Integrative Biology, vol.4, issue.7, pp.734-743, 2012. ,
Optimal network alignment with graphlet degree vectors, Cancer informatics, vol.9, p.121, 2010. ,
Netal: a new graph-based method for global alignment of protein-protein interaction networks, Bioinformatics, vol.29, issue.13, pp.1654-1662, 2013. ,
DBLP: Computer science bibliography, 2017. ,
Global network alignment using multiscale spectral signatures, Bioinformatics, vol.28, issue.23, pp.3105-3114, 2012. ,
DOI : 10.1093/bioinformatics/bts592
URL : https://academic.oup.com/bioinformatics/article-pdf/28/23/3105/6144081/bts592.pdf
Magna: maximizing accuracy in global network alignment, Bioinformatics, vol.30, issue.20, pp.2931-2940, 2014. ,
Regularizing graph centrality computations, Journal of Parallel and Distributed Computing, vol.76, pp.106-119, 2015. ,
Pairwise global alignment of protein interaction networks by matching neighborhood topology, Annual International Conference on Research in Computational Molecular Biology, pp.16-31, 2007. ,
An iterative global structure-assisted labeled network aligner, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2018. ,