Mining Maximal Adjacent Frequent Patterns from DNA Sequences using Location Information

Shuvo, Md. Tayeb Hasan; Sarja, Asif Ahmed

dc.contributor.author	Shuvo, Md. Tayeb Hasan
dc.contributor.author	Sarja, Asif Ahmed
dc.date.accessioned	2021-09-09T08:34:59Z
dc.date.available	2021-09-09T08:34:59Z
dc.date.issued	2013-11-15
dc.identifier.citation	[1] Shuang Bai, Si-Xue Bai, “The Maximal Frequent Pattern Mining of DNA Sequence”, GrC, pp 23-26, 2009. [2] T.H Kang, J.S Yoo and H, Y Kim, “Mining frequent contiguous sequence patterns in biological sequences”, in proceeding of the 7th IEEE International Conference on Bioinformatics and Bioengineering, pp 723-8, 2007. [3] R. Wanger and M. Fischer “The string-to-string Correction Problem” J. of the ACM (JACM), Vol 21, No 1, pp.168-173, 1974. [4] D. Hirschberg “Algorithms for the longest common subsequence problem” J. of the ACM (JACM). Vol 24, No 4, pp.664-675, 1977. [5] M. Garofalakis, R. Rastogi, and K. Shim, “Spirit: Sequential pattern mining with regular expression constraints.” In Proc. 1999 Int. Conf. Very Large Data Bases (VLDB’99), pages 223–234, Edinburgh, UK, Sept. 1999. [6] R. Srikant and R. Agrawal, “Mining sequential patterns: Generalizations and performance improvements.” In Proc. 5th Int. Conf. Extending Database Technology (EDBT’96), pages 3–17, Avignon, France, Mar. 1996. [7] R. Agrawal and R. Srikant, “Fast algorithms for mining association rules.” In Proc. 1994 Int. Conf. Very Large Databases (VLDB’94), pages 487–499, Santiago, Chile, Sept. 1994. [8] J. Pei, J. Han, B. Mortazavi-Asl, Q. Chen, U. Dayal, and M.C. Hsu, “PrefixSpan: Mining sequential patterns efficiently by prefix-projected pattern growth.” InICDE’01, Germany, April 2001. [9] J. Pan, p. Wang, W. Wang, B. Shi and G. Yang, “Efficient algorithms for mining maximal frequent concatenate sequences in biological datasets”, in proceeding of the fifth International Conference on Computer and Information Technology (CIT), , pp 98-104, 2005. [10] . Zerin SF, Ahmed CF, Tanbeer SK, Jeong BS, “A fast in-dexed-based contiguous sequential pattern mining tech-nique in biological data sequences.” In: Proceeding of 2nd International Conference on Emerging Databases (EBD’10), 2010 Aug 30-31, Jeju. [11] Rashid MM, Karim MR, Hossain MA, Jeong BS, “An ef-ficient approach for mining significant contiguous fre-quent patterns in biological sequences.” In: Proceeding of 3rd International Conference on Emerging Databases (EBD’11), 2011 Aug 25-27, Incheon [12] Rashid MM, Karim MR, Hossain MA, Jeong BS and -Jin Choi, “Efficient Mining of Interesting Patterns in Large Biological Sequences.” Genomics & Informatics Vol. 10(1) 44-50, March 2012 Mining Maximal Adjacent Frequent Patterns from DNA Sequences using Location Information 45 [13] Jiawei Han & Micheline Kamber , “Data Mining Concepts and Techniques”, Elsevier, 2006. [14] Pan-Ning Tan, Vipin Kumar, Michael Steinbach , “ Introduction to Data Mining”, Pearson Education Inc, 2006 [15] Ye-In Chang, Chen-Chang Wu, Jiun-Rung Chen and Yin-Han Jeng, “Mining Sequence Motifs from Motif Databasesbased on a Bit Pattern Approach”, International Journal of Innovative Computing, pp. 647-657,2012 . [16] J. Yang, W.Wang, P.S Yu and J.Han, “Mining long sequential patterns in a noisy environment”,SIGMOD, 2002	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/923
dc.description	Supervised by Tareque Mohmud Chowdhury, Assistant Professor, Department of Computer Science and Engineering (CSE) Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh.	en_US
dc.language.iso	en	en_US
dc.title	Mining Maximal Adjacent Frequent Patterns from DNA Sequences using Location Information	en_US
dc.type	Thesis	en_US