Hybrid method for the analysis of time series gene expression data

Knowledge-Based Systems

Volumn 35, Issue , 2012, Pages 14-20

  Han, Lixin ^a,b,c   Yan, Hong ^b,d  

^a HOHAI UNIVERSITY   (China)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^c NANJING UNIVERSITY   (China)

^d UNIVERSITY OF SYDNEY   (Australia)

Author keywords

Function approximation; Gene expression; K means clustering; Regression analysis; Time series analysis

Indexed keywords

COMPUTATIONAL CHALLENGES; FUNCTION APPROXIMATION; GENE EXPRESSION DATA; HYBRID METHOD; K-MEANS CLUSTERING; MULTIPLE SEGMENTATION; PIECEWISE POLYNOMIALS; POLYNOMIAL CURVE FITTING; SEGMENTATION DATA; SERIES EXPRESSION; TIME-SERIES DATA; TIME-SERIES GENE EXPRESSION DATA;

CURVE FITTING; POLYNOMIAL APPROXIMATION; REGRESSION ANALYSIS; STATISTICS; TIME SERIES ANALYSIS;

GENE EXPRESSION;

EID: 84866484337     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2012.04.003     Document Type: Article

References (39)

1. Andrew Arnold, Yan Liu, Naoki Abe, Temporal causal modeling with graphical granger methods, in: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, California, USA, August 12-15, 2007, ACM 2007, pp. 66-75. (Pubitemid 350237345)
2. Ricardo de A. Araújo A class of hybrid morphological perceptrons with application in time series forecasting Knowledge-Based Systems 24 4 2011 513 529
3. E. Hadavandi, H. Shavandi, and A. Ghanbari Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting Knowledge-Based Systems 23 8 2010 800 808
4. V. Cho MISMIS - a comprehensive decision support system for stock market investment Knowledge-Based Systems 23 6 2010 626 633
5. M.S. Khan, F. Coenen, D. Reid, R. Patel, and L. Archer A sliding windows based dual support framework for discovering emerging trends from temporal data Knowledge-Based Systems 23 4 2010 316 322
6. R.d.A. Araújo A robust automatic phase-adjustment method for financial forecasting Knowledge-Based Systems 27 2012 245 261
7. Puteri N.E. Nohuddin, Frans Coenen, Rob Christley, Christian Setzkorn, Yogesh Patel, and Shane Williams Finding "interesting" trends in social networks using frequent pattern mining and self organizing maps Knowledge-Based Systems 29 2012 104 113
8. Vit Niennattrakul, Dararat Srisai, and Chotirat Ann Ratanamahatana Shape-based template matching for time series data Knowledge-Based Systems 26 2012 1 8
9. Yi-Shian Lee, and Lee-Ing Tong Forecasting time series using a methodology based on autoregressive integrated moving average and genetic programming Knowledge-Based Systems 24 2011 66 72
10. Hailin Li, and Chonghui Guo Piecewise cloud approximation for time series mining Knowledge-Based Systems 24 2011 492 500
11. Joong Hyuk Chang Mining weighted sequential patterns in a sequence database with a time-interval weight Knowledge-Based Systems 24 2011 1 9
12. Ziv Bar-Joseph Analyzing time series gene expression data Bioinformatics 20 16 2004 2493 2503 (Pubitemid 39530134)
13. Nitai D. Mukhopadhyay, and Snigdhansu Chatterjee Causality and pathway search in microarray time series experiment Bioinformatics 23 4 2007 442 449 (Pubitemid 46331215)
14. Aurélie C. Lozano, Naoki Abe, Yan Liu, and Saharon Rosset Grouped graphical Granger modeling for gene expression regulatory networks discovery Bioinformatics 25 12 2009 i110 i118
15. Soosung Hwang, and Pedro L. Valls Pereira The effects of structural breaks in ARCH and GARCH parameters on persistence of GARCH models Communications in Statistics - Simulation and Computation 37 3 2008 571 578
16. Robert F. Engle Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation Econometrica 50 4 1982 987 1007
17. Tim Bollerslev Generalized autoregressive conditional heteroskedasticity Journal of Econometrics 31 1986 307 327
18. Paolo Magni, Fulvia Ferrazzi, Lucia Sacchi, and Riccardo Bellazzi TimeClust: a clustering tool for gene expression time series Bioinformatics 24 3 2008 430 432 (Pubitemid 351189023)
19. Fulvia Ferrazzi, Paolo Magni, and Riccardo Bellazzi Random walk models for Bayesian clustering of gene expression profiles Applied Bioinformatics 4 4 2005 263 276 (14) (Pubitemid 41737128)
20. L. Sacchi, R. Bellazzi, C. Larizza, P. Magni, T. Curk, U. Petrovic, and B. Zupan TA-Clustering: cluster analysis of gene expression profiles through temporal abstractions International Journal of Medical Informatics 74 7-8 2005 505 517 (Pubitemid 41021914)
21. Rong Jiang, and Hong Yan Studies of spectral properties of short genes using the wavelet subspace Hilbert-Huang transform (WSHHT) Physica A: Statistical Mechanics and its Applications 387 16-17 2008 4223 4247
22. Chao-Chun Liu, Dao-Qing Dai, and Hong Yan The theoretic framework of local weighted approximation for microarray missing value estimation Pattern Recognition 43 8 2010 2993 3002
23. Wei-Feng Zhang, Chao-Chun Liu, and Hong Yan Clustering of temporal gene expression data by regularized spline regression and an energy based similarity measure Pattern Recognition 43 12 2010 3969 3976
24. Tien-ho Lin, Naftali Kaminski, and Ziv Bar-Joseph Alignment and classification of time series gene expression in clinical studies Bioinformatics 24 13 2008 i147 i155
25. Adam A. Smith, Aaron Vollrath, Christopher A. Bradfield, and Mark Craven Clustered alignments of gene-expression time series data Bioinformatics 25 12 2009 i119 i1127
26. http://pages.cs.wisc.edu/~aasmith/smith-dissertation.pdf, 2009.
27. Chang-Tsun Li, Yinyin Yuan, and Roland Wilson An unsupervised conditional random fields approach for clustering gene expression time series Bioinformatics 24 21 2008 2467 2473
28. Gautam Goel, I-Chun Chou, and Eberhard O. Voit System estimation from metabolic time-series data Bioinformatics 24 21 2008 2505 2511
29. Jongrae Kim, Declan G. Bates, Ian Postlethwaite, Pat Heslop-Harrison, and Kwang-Hyun Cho Linear time-varying models can reveal non-linear interactions of biomolecular regulatory networks using multiple time-series data Bioinformatics 24 10 2008 1286 1292 (Pubitemid 351659626)
30. Peter Gennemark, and Dag Wedelin Benchmarks for identification of ordinary differential equations from time series data Bioinformatics 25 6 2009 780 786
31. Ivan G. Costa, Alexander Schönhuth, Christoph Hafemeister, and Alexander Schliep Constrained mixture estimation for analysis and robust classification of clinical time series Bioinformatics 25 12 2009 i6 i14
32. Filip Hermans, and Elena Tsiporkova Merging microarray cell synchronization experiments through curve alignment Bioinformatics 23 2 2007 e64 e70
33. Matthias E. Futschik, and Hanspeter Herzel Are we overestimating the number of cell-cycling genes? The impact of background models on time-series analysis Bioinformatics 24 8 2008 1063 1069 (Pubitemid 351514056)
34. Elena Tsiporkova, and Veselka Boeva Fusing time series expression data through hybrid aggregation and hierarchical merge Bioinformatics 24 16 2008 i63 i69
35. S. Chatterjee, and A.S. Hadi Influential observations, high leverage points, and outliers in linear regression Statistical Science 1986 379 416
36. Kecun Zhang, and Yingliang Zhao Algorithm and Analysis for Numerical Calculation 2003 Science Press Beijing
37. C. de Boor A Practical Guide to Splines 1978 Springer-Verlag
38. Paul T. Spellman, Gavin Sherlock, Michael Q. Zhang, Vishwanath R. Iyer, Kirk Anders, Michael B. Eisen, Patrick O. Brown, David Botstein, and Bruce Futcher Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization Molecular Biology of the Cell 9 12 1998 3273 3297 (Pubitemid 28551928)
39. http://genome-www.stanford.edu/, 1999.