Metasample-based sparse representation for tumor classification

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 8, Issue 5, 2011, Pages 1273-1282

  Zheng, Chun Hou ^a,b   Zhang, Lei ^b   Ng, To Yee ^b   Shiu, Chi Keung ^b   Huang, De Shuang ^c  

^a QUFU NORMAL UNIVERSITY   (China)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^c TONGJI UNIVERSITY   (China)

Author keywords

gene expression data; metasample; sparse representation; Tumors classification

Indexed keywords

GENE EXPRESSION DATA; INCOMPLETE MEASUREMENTS; LINEAR COMBINATIONS; METASAMPLE; REGULARIZED LEAST SQUARES; SPARSE REPRESENTATION; SPARSE SOLUTIONS; TESTING SAMPLES; TRAINING SAMPLE; TUMOR CLASSIFICATION;

EXTRACTION; GENE EXPRESSION; LEAST SQUARES APPROXIMATIONS; TUMORS;

CLASSIFICATION (OF INFORMATION);

ARTICLE; BIOLOGY; CLASSIFICATION; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETIC DATABASE; GENETICS; HUMAN; METABOLISM; METHODOLOGY; NEOPLASM; REPRODUCIBILITY; SUPPORT VECTOR MACHINE;

COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; GENE EXPRESSION PROFILING; HUMANS; NEOPLASMS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REPRODUCIBILITY OF RESULTS; SUPPORT VECTOR MACHINES;

EID: 79960919498     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2011.20     Document Type: Article

References (40)

1. P.O. Brown and D. Botstein, "Exploring the New World of the Genome with DNA Microarray," The Chipping Forest, vol. 21, pp. 33-37, 1999. (Pubitemid 29031489)
2. E.E. Ntzani and J.P. Ioannidis, "Predictive Ability of DNA Microarrays for Cancer Outcomes and Correlates: An Empirical Assessment," Lancet, vol. 362, pp. 1439-1444, 2003. (Pubitemid 37352879)
3. T.R. Golub et al., "Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring," Science, vol. 286, pp. 531-537, 1999.
4. U. Alon, N. Barkai, D.A. Notterman, K. Gish, S. Ybarra, D. Mack, and A.J. Levine, "Broad Patterns of Gene Expression Revealed by Clustering Analysis of Tumor and Normal Colon Tissues Probed by Oligonucleotide Arrays," Proc. Nat'l Academy of Sciences USA, vol. 96, pp. 6745-6750, 1999. (Pubitemid 29274954)
5. J.P. Brunet, P. Tamayo, T.R. Golun, and J.P. Mesirov, "Metagenes and Molecular Pattern Discovery Using Matrix Factorization," Proc Nat'l Academy of Sciences of USA, vol. 101, no. 12, pp. 4164-416, 2004.
6. T.K. Paul and H. Iba, "Prediction of Cancer Class with Majority Voting Genetic Programming Classifier Using Gene Expression Data," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 6, no. 2, pp. 353-367, Apr.-June 2009.
7. K. Bryan, P. Cunningham, and N. Bolshakova, "Application of Simulated Annealing to the Biclustering of Gene Expression Data," IEEE Trans. Information Technology in Biomedicine, vol. 10, no. 3, pp. 519-525, July 2006. (Pubitemid 44194083)
8. Y. Gao and C. George, "Improving Molecular Cancer Class Discovery through Sparse Non-Negative Matrix Factorization," Bioinformatics, vol. 21, pp. 3970-3975, 2005. (Pubitemid 41631836)
9. D.S. Huang and C.H. Zheng, "Independent Component Analysis-Based Penalized Discriminant Method for Tumor Classification Using Gene Expression Data," Bioinformatics, vol. 22, pp. 1855-1862, 2006.
10. Y. Tang, Y. Zhang, and Z. Huang, "Development of Two-Stage SVM-RFE Gene Selection Strategy for Microarray Expression Data Analysis," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 4, no. 3, pp. 365-381, July-Sept. 2007. (Pubitemid 47274713)
11. J. Reunanen, "Overfitting in Making Comparisons between Variable Selection Methods," J. Machine Learning Research, vol. 3, pp. 1371-1382, 2003.
12. S.S. Chen, D.L. Donoho, and M.A. Saunders, "Atomic Decomposition by Basis Pursuit," SIAM Review, vol. 43, no. 1, pp. 129-159, 2001. (Pubitemid 32406896)
13. E.J. Candès, J. Romberg, and T. Tao, "Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information," IEEE Trans. Information Theory, vol. 52, no. 2, pp. 489-509, Feb. 2006. (Pubitemid 43174093)
14. E.J. Candès and T. Tao, "Near-Optimal Signal Recovery from Random Projections: Universal Encoding Strategies?" IEEE Trans. Information Theory, vol. 52, no. 12, pp. 5406-5425, Dec. 2006. (Pubitemid 46445381)
15. D.L. Donoho, "Compressed Sensing," IEEE Trans. Information Theory, vol. 52, no. 4, pp. 1289-1306, Apr. 2006.
16. R. Tibshirani, "Regression Shrinkage and Selection via the Lasso," J. Royal Statistical Soc. Series B, vol. 58, no. 1, pp. 267-288, 1996.
17. S.-J. Kim, K. Koh, M. Lustig, S. Boyd, and D. Gorinevsky, "An Interior-Point Method for Large-Scale l1-Regularized Least Squares," IEEE J. Selected Topics in Signal Processing, vol. 1, no. 4, pp. 606-617, Dec. 2007. (Pubitemid 351266626)
18. J. Wright, A.Y. Yang, A. Ganesh, S.S. Sastry, and Y. Ma, "Robust Face Recognition via Sparse Representation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, no. 2, pp. 210-227, Feb. 2009.
19. X. Hang and F.X. Wu, "Sparse Representation for Classification of Tumors Using Gene Expression Data," J. Biomedicine and Biotechnology, vol. 2009, p. 6., 2009.
20. P. Belhumeur, J. Hespanda, and D. Kriegman, "Eigenfaces versus Fisherfaces: Recognition Using Class Specific Linear Projection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 711-720, July 1997. (Pubitemid 127762263)
21. C.H. Zheng, D.S. Huang, L. Zhang, and X.Z. Kong, "Tumor Clustering Using Non-Negative Matrix Factorization with Gene Selection," IEEE Trans. Information Technology in Biomedicine, vol. 13, no. 4, pp. 599-607, July 2009.
22. O. Alter, P.O. Brown, and D. Botstein, "Singular Value Decomposition for Genome-Wide Expression Data Processing and Modeling," Proc. Nat'l Academy of Sciences USA, vol. 97, pp. 10101-10106, 2000.
23. W. Liebermeister, "Linear Modes of Gene Expression Determined by Independent Component Analysis," Bioinformatics, vol. 18, pp. 51-60, 2002. (Pubitemid 34145031)
24. C.H. Zheng, D.S. Huang, K. Li, G. Irwin, and Z.L. Sun, "MISEP Method for Post-Nonlinear Blind Source Separation," Neural Computation, vol. 19, no. 9, pp. 2557-2578, 2007.
25. H.Q. Wang and D.S. Huang, "Regulation Probability Method for Gene Selection," Pattern Recognition Letter, vol. 27, no. 2, pp. 116-122, 2006.
26. H.Q. Wang, H.S. Wong, D.S. Huang, and J. Shu, "Extracting Gene Regulation Information for Cancer Classification," Pattern Recognition, vol. 40, pp. 3379-3392, 2007. (Pubitemid 47223286)
27. E. Amaldi and V. Kann, "On the Approximability of Minimizing Nonzero Variables or Unsatisfied Relations in Linear Systems," Theoretical Computer Science, vol. 209, pp. 237-260, 1998. (Pubitemid 128450440)
28. T.S. Furey, N. Cristianini, N. Duffy, D.W. Bednarski, M. Schummer, and D. Haussler, "Support Vector Machines Classification and Validation of Cancer Tissue Samples Using Microarray Expression Data," Bioinformatics, vol. 16, pp. 906-914, 2000.
29. A. Statnikov, C.F. Aliferis, I. Tsamardinos, D. Hardin, and S. Levy, "A Comprehensive Evaluation of Multicategory Classification Methods for Microarray Gene Expression Cancer Diagnosis," Bioinformatics, vol. 21, no. 5, pp. 631-643, 2005. (Pubitemid 40424789)
30. N. Pochet, F. De Smet, J.A.K. Suykens, and B.L.R. De Moor, "Systematic Benchmarking of Microarray Data Classification: Assessing the Role of Non-Linearity and Dimensionality Reduction," Bioinformatics, vol. 20, pp. 3185-3195, 2004. (Pubitemid 39619208)
31. J.E. Staunton et al., "Chemosensitivity Prediction by Transcriptional Profiling," Proc. Nat'l Academy of Sciences USA, vol. 98, no. 19, pp. 10787-10792, 2001. (Pubitemid 32878698)
32. A.I. Su et al., "Molecular Classification of Human Carcinomas by Use of Gene Expression Signatures," Cancer Research, vol. 61, no. 20, pp. 7388-7393, 2001. (Pubitemid 32995021)
33. S.A. Armstrong, J.E. Staunton, L.B. Silverman, R. Pieters, M.L. den Boer, M.D. Minden, S.E. Sallan, E.S. Lander, T.R. Golub, and S.J. Korsmeyer, "MLL Translocations Specify a Distinct Gene Expression Profile that Distinguishes a Unique Leukemia," Nature Genetics, vol. 30, pp. 41-47, 2002.
34. A. Bhattacharjee et al., "Classification of Human Lung Carcinomas by mRNA Expression Profiling Reveals Distinct Adenocarcinoma Subclasses," Proc. Nat'l Academy of Sciences USA, vol. 98, pp. 13790-13795, 2001. (Pubitemid 33115977)
35. J. Khan, J.S. Wei, M. Ringner, L.H. Saal, M. Ladanyi, F. Westermann, F. Berthold, M. Schwab, C.R. Antonescu, C. Peterson, and P.S. Meltzer, "Classification and Diagnostic Prediction of Cancers Using Gene Expression Profiling and Artificial Neural Networks," Nature Medicine, vol. 7, no. 6, pp. 673-679, 2001. (Pubitemid 32588022)
36. M.A. Shipp et al., "Diffuse Large B-Cell Lymphoma Outcome Prediction by Gene Expression Profiling and Supervised Machine Learning," Nature Medicine, vol. 8, no. 1, pp. 68-74, 2002. (Pubitemid 34101731)
37. D. Singh et al., "Gene Expression Correlates of Clinical Prostate Cancer Behavior," Cancer Cell, vol. 1, pp. 203-209, 2002. (Pubitemid 41039166)
38. S. Dudoit, J. Fridlyand, and T.P. Speed, "Comparison of Discrimination Methods for the Classification of Tumor Using Gene Expression Data," J. Am. Statistical Assoc., vol. 97, pp. 77-87, 2002.
39. S.L. Wang, X. Li, S. Zhang, J. Gui, and D.S. Huang, "Tumor Classification by Combining PNN Classifier Ensemble with Neighborhood Rough Set Based Gene Reduction," Computers in Biology and Medicine, vol. 40, no. 2, pp. 179-189, 2010.
40. D. Ghosh and A.M. Chinnaiyan, "Classification and Selection of Biomarkers in Genomic Data Using LASSO," J. Biomedicine and Biotechnology, vol. 2, pp. 147-154, 2005. (Pubitemid 41627871)