The Graph Motif Problem Parameterized by the Structure of the Input Graph

Authors Édouard Bonnet, Florian Sikora



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Édouard Bonnet
Florian Sikora

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Édouard Bonnet and Florian Sikora. The Graph Motif Problem Parameterized by the Structure of the Input Graph. In 10th International Symposium on Parameterized and Exact Computation (IPEC 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 43, pp. 319-330, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)
https://doi.org/10.4230/LIPIcs.IPEC.2015.319

Abstract

The Graph Motif problem was introduced in 2006 in the context of biological networks. It consists of deciding whether or not a multiset of colors occurs in a connected subgraph of a vertex-colored graph. Graph Motif has been analyzed from the standpoint of parameterized complexity. The main parameters which came into consideration were the size of the multiset and the number of colors. Though, in the many applications of Graph Motif, the input graph originates from real-life and has structure. Motivated by this prosaic observation, we systematically study its complexity relatively to graph structural parameters. For a wide range of parameters, we give new or improved FPT algorithms, or show that the problem remains intractable. Interestingly, we establish that Graph Motif is W[1]-hard (while in W[P]) for parameter max leaf number, which is, to the best of our knowledge, the first problem to behave this way.
Keywords
  • Parameterized Complexity
  • Structural Parameters
  • Graph Motif
  • Computational Biology

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References

  1. Eric Alm and Adam P. Arkin. Biological Networks. Current Opinion in Structural Biology, 13(2):193-202, 2003. Google Scholar
  2. Abhimanyu M. Ambalath, Radheshyam Balasundaram, Chintan Rao H., Venkata Koppula, Neeldhara Misra, Geevarghese Philip, and M. S. Ramanujan. On the Kernelization Complexity of Colorful Motifs. In Proc. of the 5th IPEC, volume 6478 of LNCS, pages 14-25. Springer, 2010. Google Scholar
  3. Daniel Berend and Tamir Tassa. Improved bounds on bell numbers and on moments of sums of random variables. Probab. and Math. Statist., 30(2):185-205, 2010. Google Scholar
  4. Nadja Betzler, René van Bevern, Michael R. Fellows, Christian Komusiewicz, and Rolf Niedermeier. Parameterized algorithmics for finding connected motifs in biological networks. IEEE/ACM Trans. Comput. Biology Bioinform., 8(5):1296-1308, 2011. Google Scholar
  5. Andreas Björklund, Petteri Kaski, and Lukasz Kowalik. Probably optimal graph motifs. In Proc. of the 30th International Symposium on Theoretical Aspects of Computer Science (STACS), volume 20 of LIPIcs, 2012. Google Scholar
  6. Andreas Björklund, Petteri Kaski, Lukasz Kowalik, and Juho Lauri. Engineering motif search for large graphs. In Ulrik Brandes and David Eppstein, editors, Proc. of the 17th ALENEX, pages 104-118. SIAM, 2015. Google Scholar
  7. Sebastian Böcker. A golden ratio parameterized algorithm for cluster editing. J. Discrete Algorithms, 16:79-89, 2012. Google Scholar
  8. Sebastian Böcker, Florian Rasche, and Tamara Steijger. Annotating Fragmentation Patterns. In Proc. of the 9th International Workshop Algorithms in Bioinformatics (WABI), volume 5724 of LNCS, pages 13-24. Springer, 2009. Google Scholar
  9. Hans L. Bodlaender, Bart M. P. Jansen, and Stefan Kratsch. Kernelization lower bounds by cross-composition. SIAM J. Discrete Math., 28(1):277-305, 2014. Google Scholar
  10. Sharon Bruckner, Falk Hüffner, Richard M. Karp, Ron Shamir, and Roded Sharan. Topology-Free Querying of Protein Interaction Networks. Journal of Computational Biology, 17(3):237-252, 2010. Google Scholar
  11. Jianer Chen, Iyad A. Kanj, and Ge Xia. Improved upper bounds for vertex cover. Theoretical Computer Science, 411(40–42):3736 - 3756, 2010. Google Scholar
  12. Marek Cygan, Marcin Pilipczuk, and Michal Pilipczuk. Known algorithms for EDGE CLIQUE COVER are probably optimal. In Proc. of Symposium on Discrete Algorithms, SODA 2013, pages 1044-1053. SIAM, 2013. Google Scholar
  13. Riccardo Dondi, Guillaume Fertin, and Stéphane Vialette. Complexity issues in vertex-colored graph pattern matching. J Discr Algo, 9(1):82-99, 2011. Google Scholar
  14. Rodney G. Downey and Michael R. Fellows. Fundamentals of Parameterized Complexity. Springer, 2013. Google Scholar
  15. Michael R. Fellows, Guillaume Fertin, Danny Hermelin, and Stéphane Vialette. Upper and lower bounds for finding connected motifs in vertex-colored graphs. J. Comput. Syst. Sci., 77(4):799-811, 2011. Google Scholar
  16. Michael R. Fellows, Daniel Lokshtanov, Neeldhara Misra, Matthias Mnich, Frances A. Rosamond, and Saket Saurabh. The complexity ecology of parameters: An illustration using bounded max leaf number. Theory Comput. Syst., 45(4):822-848, 2009. Google Scholar
  17. Robert Ganian. Twin-cover: Beyond vertex cover in parameterized algorithmics. In Proc. of the 6th International Symposium Parameterized and Exact Computation IPEC 2011, volume 7112 of LNCS, pages 259-271. Springer, 2011. Google Scholar
  18. Robert Ganian. Using neighborhood diversity to solve hard problems. CoRR, abs/1201.3091, 2012. Google Scholar
  19. Jens Gramm, Jiong Guo, Falk Hüffner, and Rolf Niedermeier. Data reduction and exact algorithms for clique cover. ACM Journal of Experimental Algorithmics, 13, 2008. Google Scholar
  20. Sylvain Guillemot and Florian Sikora. Finding and counting vertex-colored subtrees. Algorithmica, 65(4):828-844, 2013. Google Scholar
  21. Russell Impagliazzo, Ramamohan Paturi, and Francis Zane. Which problems have strongly exponential complexity? J. Comput. Syst. Sci., 63(4):512-530, 2001. Google Scholar
  22. Christian Komusiewicz and Rolf Niedermeier. New races in parameterized algorithmics. In Proc. of Mathematical Foundations of Computer Science MFCS 2012, volume 7464 of LNCS, pages 19-30. Springer, 2012. Google Scholar
  23. Ioannis Koutis. Constrained multilinear detection for faster functional motif discovery. Inf. Process. Lett., 112(22):889-892, 2012. Google Scholar
  24. Vincent Lacroix, Cristina G. Fernandes, and Marie-France Sagot. Motif search in graphs: application to metabolic networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 3(4):360-368, 2006. Google Scholar
  25. Michael Lampis. Algorithmic meta-theorems for restrictions of treewidth. Algorithmica, 64(1):19-37, 2012. Google Scholar
  26. Daniel Lokshtanov, Dániel Marx, and Saket Saurabh. Slightly superexponential parameterized problems. In Proc. of SODA 2011, pages 760-776, 2011. Google Scholar
  27. Carsten Lund and Mihalis Yannakakis. On the hardness of approximating minimization problems. J. ACM, 41(5):960-981, 1994. Google Scholar
  28. Rolf Niedermeier. Invitation to Fixed Parameter Algorithms. Lecture Series in Mathematics and Its Applications. Oxford University Press, 2006. Google Scholar
  29. Ron Y. Pinter, Hadas Shachnai, and Meirav Zehavi. Deterministic parameterized algorithms for the graph motif problem. In Proc. of Mathematical Foundations of Computer Science MFCS 2014, volume 8635 of LNCS, pages 589-600. Springer, 2014. Google Scholar
  30. Ron Y. Pinter and Meirav Zehavi. Algorithms for topology-free and alignment network queries. J. Discrete Algorithms, 27:29-53, 2014. Google Scholar
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