Trie-based apriori motif discovery approach

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7292 LNBI, Issue , 2012, Pages 1-12

  Al Turaiki, Isra ^a   Badr, Ghada ^a   Mathkour, Hassan ^a  

^a KING SAUD UNIVERSITY   (Saudi Arabia)

Author keywords

Apriori; Bioinformatics; data mining; DNA; motif discovery; Suffix trees; Transcription factor binding site; Tries

Indexed keywords

APRIORI; MOTIF DISCOVERY; SUFFIX-TREES; TRANSCRIPTION FACTOR BINDING SITES; TRIES;

ALGORITHMS; BENCHMARKING; DATA MINING; DATA STRUCTURES; DNA; TRANSCRIPTION FACTORS;

BIOINFORMATICS;

EID: 84861131207     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-30191-9_1     Document Type: Conference Paper

References (23)

1. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: Proceedings of the 20th International Conference on Very Large Data Bases, San Francisco, CA, USA, pp. 487-499 (1994)
2. Badr, G.: Tries in information retrieval and syntactic pattern recognition. Ph.D. Thesis, School of Computer Science, Carleton University (June 2006)
3. Badr, G., Turcotte, M.: Component-Based Matching for Multiple Interacting RNA Sequences. In: Chen, J., Wang, J., Zelikovsky, A. (eds.) ISBRA 2011. LNCS, vol. 6674, pp. 73-86. Springer, Heidelberg (2011)
4. Bailey, T.L., Elkan, C.: Fitting a mixture model by expectation maximization to discover motifs in biopolymers. In: Proceedings of International Conference on Intelligent Systems for Molecular Biology, ISMB, vol. 2, pp. 28-36 (1994)
5. Bajcsy, P., Han, J., Liu, L., Yang, J.: Survey of biodata analysis from a data mining perspective. In: Wu, X., Jain, L., Wang, J.T., Zaki, M.J., Toivonen, H.T., Shasha, D. (eds.) Data Mining in Bioinformatics, pp. 9-39. Springer, London (2005)
6. Carvalho, A.M., Freitas, A.T., Oliveira, A.L., Sagot, M.: An efficient algorithm for the identification of structured motifs in DNA promoter sequences. IEEE/ACM Trans. Comput. Biol. Bioinformatics 3(2), 126-140 (2006)
7. Goos, G., Hartmanis, J., Leeuwen, J., Crochemore, M., Iliopoulos, C.S., Mohamed, M., Sagot, M.: Longest Repeats with a Block of Don't Cares. In: Farach-Colton, M. (ed.) LATIN 2004. LNCS, vol. 2976, pp. 271-278. Springer, Heidelberg (2004)
8. Jiang, H., Zhao, Y., Chen, W., Zheng, W.: Searching maximal degenerate motifs guided by a compact suffix tree. Advances in Experimental Medicine and Biology 680, 19-26 (2010)
9. Li, M., Ma, B., Wang, L.: Finding similar regions in many sequences. Journal of Computer and System Sciences 65, 73-96 (2002)
10. Matys, V., Kel-Margoulis, O.V., Fricke, E., Liebich, I., Land, S., Barre-Dirrie, A., Reuter, I., Chekmenev, D., Krull, M., Hornischer, K., Voss, N., Stegmaier, P., Lewicki-Potapov, B., Saxel, H., Kel, A.E., Wingender, E.: TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes. Nucleic Acids Research 34(Database issue), D108-D110 (2006)
11. Ozer, H.G., Ray,W.C.: Informative Motifs in Protein Family Alignments. In: Giancarlo, R., Hannenhalli, S. (eds.) WABI 2007. LNCS (LNBI), vol. 4645, pp. 161-170. Springer, Heidelberg (2007)
12. Pavesi, G., Mauri, G., Pesole, G.: An algorithm for finding signals of unknown length in DNA sequences. Bioinformatics 17(suppl. 1), S207-S214 (2001)
13. Pavesi, G., Mauri, G., Pesole, G.: In silico representation and discovery of transcription factor binding sites. Briefings in Bioinformatics 5(3), 217-236 (2004)
14. Pevzner, P.A., Sze, S.H.: Combinatorial approaches to finding subtle signals in DNA sequences. In: Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, pp. 269-278. AAAI Press (2000)
15. Sagot, M.-F.: Spelling Approximate Repeated or Common Motifs Using a Suffix Tree. In: Lucchesi, C.L., Moura, A.V. (eds.) LATIN 1998. LNCS, vol. 1380, pp. 374-390. Springer, Heidelberg (1998)
16. Sagot, M.F., Escalier, V., Viari, A., Soldano, H.: Searching for repeated words in a text allowing for mismatches and gaps. In: Baeza-Yates, R., Manber, U. (eds.) Second South American Workshop on String Processing, pp. 87-100. University of Chile (1995)
17. Sandelin, A., Alkema, W., Engstrm, P., Wasserman, W.W., Lenhard, B.: JASPAR: an open-access database for eukaryotic transcription factor binding profiles. Nucleic Acids Research 32(Database issue), D91-D94 (2004)
18. Schneider, T.D., Stormo, G.D., Gold, L.: Information content of binding sites on nucleotide sequences. Journal of Molecular Biology 188(3), 415-431 (1986)
19. Tompa, M., Li, N., Bailey, T.L., Church, G.M., De Moor, B., Eskin, E., Favorov, A.V., Frith, M.C., Fu, Y., Kent, W.J., Makeev, V.J., Mironov, A.A., Noble, W.S., Pavesi, G., Pesole, G., Rgnier, M., Simonis, N., Sinha, S., Thijs, G., van Helden, J., Vandenbogaert, M., Weng, Z., Workman, C., Ye, C., Zhu, Z.: Assessing computational tools for the discovery of transcription factor binding sites. Nature Biotechnology 23(1), 137-144 (2005)
20. Ukkonen, E.: On-Line construction of suffix trees. Algorithmica 14, 249-260 (1995)
21. Weiner, P.: Linear pattern matching algorithms. In: IEEE Conference Record of 14th Annual Symposium on Switching and Automata Theory, SWAT 2008, pp. 1-11. IEEE (October 1973)
22. Wijaya, E., Rajaraman, K., Yiu, S., Sung, W.: Detection of generic spaced motifs using submotif pattern mining. Bioinformatics 23(12), 1476-1485 (2007)
23. Jia, C., Lu, R., Chen, L.: A Frequent PatternMining Method for Finding Planted (l, d)-motifs of Unknown Length. In: Yu, J., Greco, S., Lingras, P.,Wang, G., Skowron, A. (eds.) RSKT 2010. LNCS, vol. 6401, pp. 240-248. Springer, Heidelberg (2010)