Optimal segmentation using tree models

Knowledge and Information Systems

Volumn 15, Issue 3, 2008, Pages 259-283

  Gwadera, Robert ^a   Gionis, Aristides ^a   Mannila, Heikki ^a  

^a HELSINKI INSTITUTE FOR INFORMATION TECHNOLOGY   (Finland)

Author keywords

DNA segmentation; MDL; Sequence data mining; Sequence segmentation

Indexed keywords

FORESTRY; MARKOV CHAINS;

BAYESIAN INFORMATION CRITERION; COMPUTATIONAL BIOLOGY; ENVIRONMENTAL SCIENCE; MINIMUM DESCRIPTION LENGTH PRINCIPLE; OPTIMAL SEGMENTATION; SEGMENTAL STRUCTURE; SEQUENCE-DATA MINING; VARIABLE LENGTH MARKOV CHAINS;

DATA MINING;

EID: 44649089301     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-007-0091-5     Document Type: Article

References (29)

1. Barron A, Rissanen J and Yu B (1998). The minimum desiption length principle in coding and modeling. IEEE Trans Inf Theory 44(6): 2743-2760
2. Bellman R (1961). On the approximation of curves by line segments using dynamic programming. Commun ACM 4(6): 284
3. Bernaola-Galvan P, Grosse I, Carpena P, Oliver J, Roman-Roland R and Stanley H (2000). Finding borders between coding and noncoding dna regions by an entropic segmentation method. Phys Rev Lett 85(6): 1342-1345
4. Braun J and Muller H (1998). Statistical methods for dna sequence segmentation. Statist Sci 13(2): 142-162
5. Bühlmann P and Wyner A (1999). Variable length Markov chains. Ann Statist 27: 480-513
6. Burge Ch and Karlin S (1997). Prediction of complete gene structures in human genomic dna. J Mol Biol 268: 78-94
7. Csiszar I and Talata Z (2006). Context tree estimation for not necessarily finite memory processes, via bic and mdl. IEEE Trans Inf Theory 52(3): 1007-1016
8. Grünwald P (2005) A tutorial introduction to the minimum description length principle. In: Advances in minimum description length: Theory and applications. MIT Press
9. Guigo R and Fickett J (1995). Distinctive sequence features in protein coding genic non-coding and intergenic human dna. J Mol Biol 253: 51-60
10. Hansen M and Yu B (2001). Model selection and the principle of minimum description length. J Am Statist Assoc 96(454): 746-774
11. Herzel H and Grosse I (1997). Correlations in dna sequences: The role of protein coding segments. Phys Rev Lett 55(1): 800-810
12. Mannila H, Tikanmki J, Himberg J, Korpiaho K, Toivonen H (2001) Time series segmentation for context recognition in mobile devices. In: First IEEE international conference on data mining, pp 203-210
13. Kehagias Ath (2004). A hidden markov model segmentation procedure for hydrological and environmental time series. Stoch Environ Res Risk Assess (SERRA) 18(2): 117-130
14. Keogh EJ, Chu S, Hart D, Pazzani MJ (2001) An online algorithm for segmenting time series. In: ICDM, pp 289-296
15. Krichevsky R and Trofimov V (1981). The performance of universal encoding. IEEE Trans Inf Theory IT-27(2): 199-207
16. Li W (2001) DNA segmentation as a model selection process. In: International conference on research in computational molecular biology, pp 204-210
17. Liu S and Lawrence C (1999). Bayesian inference of biopolymer models. Bioinformatic 15: 38-52
18. Makeev V, Ramensky V, Gelfand M, Roytberg M, Tumanyan V (2000) Bayesian approach to dna segmentation into regions with different average nucleotide composition. Lecture Notes in Computer Science, 2066:54-73, Computational Biology
19. Orlov Y, Potapov V, Filipov V (2002) Recognizing functional dna sites and segmenting genomes using the program "complexity". In: Proceedings of BGRS 2002, vol 3. Novosibirsk Insititute of Cytology and Genetics Press, pp 244-247
20. Henderson D, Boys R and Wilkinson D (2000). Detecting homogeneous segments in dna sequences by using hidden markov models. Appl Statist 49(2): 269-285
21. Rissanen J (1983). A universal data compression system. IEEE Trans Inf Theory IT-29(5): 656-664
22. Rissanen J (1999). Fast universal coding with context models. IEEE Trans Inf Theory 45(4): 1065-1071
23. Salmenkivi M and Mannila H (2005). Using markov chain monte carlo and dynamic programming for event sequence data. Knowl Inf Systems 7(3): 267-288
24. Schwarz G (1978). Estimating the dimension of a model. Ann Statist 7(2): 461-464
25. Szpankowski W, Ren W, Szpankowski L (2003) An optimal DNA segmentation based on the MDL principle. In: IEEE computer society bioinformatics conference, pp 541-546
26. Weinberger M, Rissanen J and Feder M (1995). A universal finite memory source. IEEE Trans Inf Theory 41(3): 643-652
27. Willems F, Shtarkov Y and Tjalkens T (1995). The context-tree weighting method: Basic properties. IEEE Trans Inf Theory IT-41: 653-664
28. Willems F, Shtarkov Y, Tjalkens T (2000) Context tree maximizing. In: Conference on information sciences and systems, pp 7-12
29. Zhang M (1998). Statistical features of human exons and their flanking regions. Hum Mol Genet 7(5): 919-932