Gene classification using parameter-free semi-supervised manifold learning

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 9, Issue 3, 2012, Pages 818-827

  Huang, Hong ^a   Feng, Hailiang ^a  

^a CHONGQING UNIVERSITY   (China)

Author keywords

Dimensionality reduction; Gene expression data; Parameter free; Semi supervised local Fisher discriminant analysis; Uncorrelated constraint

Indexed keywords

DIMENSIONALITY REDUCTION; GENE EXPRESSION DATA; PARAMETER FREE; SEMI-SUPERVISED; UNCORRELATED CONSTRAINT;

FISHER INFORMATION MATRIX;

GENE EXPRESSION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; CLASSIFICATION; GENE; GENE EXPRESSION; GENETICS; NEOPLASM;

ALGORITHMS; GENE EXPRESSION; GENES; NEOPLASMS; PATTERN RECOGNITION, AUTOMATED;

EID: 84859198391     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2011.152     Document Type: Article

References (23)

1. Q. Cheng, "A Sparse Learning Machine for High-Dimensional Data with Application to Microarray Gene Analysis," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 7, no. 4, pp. 636-646, Oct.-Dec. 2010.
2. Y.P. Li, X.H. Hu, H.F. Lin, and Z.H. Yang, "A Framework for Semisupervised Feature Generation and Its Applications in Biomedical Literature Mining," IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 8, no. 2, pp. 294-307, Mar./Apr. 2011.
3. J.G. Lee and C.S. Zhang, "Classification of Gene-Expression Gata: The Manifold-Based Metric Learning Way," Pattern Recognition, vol. 39, no. 12, pp. 2450-2463, 2006.
4. L.X. Zhao and Z.Y. Zhang, "Supervised Locally Linear Embedding with Probability-Based Distance for Classification," Computers and Math. with Applications, vol. 57, no. 6, pp. 919-926, 2009.
5. S.T. Roweis and L.K. Saul, "Nonlinear Dimensionality Reduction by Locally Linear Embedding," Science, vol. 290, no. 5500, pp. 2323-2326, 2000. (Pubitemid 32041578)
6. J.B. Tenenbaum, V. de Silva, and J.C. Langford, "A Global Geometric Framework for Nonlinear Dimensionality Reduction," Science, vol. 290, no. 5500, pp. 2319-2323, 2000. (Pubitemid 32041577)
7. M. Belkin and P. Niyogi, "Laplacian Eigenmaps for Dimensionality Reduction and Data Representation," Neural Computation, vol. 15, no. 6, pp. 1373-1396, 2003. (Pubitemid 37049796)
8. Z.Y. Zhang and H.Y. Zha, "Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment," SIAM J. Scientific Computing, vol. 26, no. 1, pp. 313-338, 2005.
9. X.F. He, S.C. Yan, Y. Hu, P. Niyogi, and H.J. Zhang, "Face Recognition Using Laplacianfaces," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 3, pp. 328-340, Mar. 2010. (Pubitemid 40377326)
10. X.F. He et al., "Neighborhood Preserving Embedding," Proc. IEEE 10th Int'l Conf. Computer Vision, pp. 1208-1213, 2005.
11. S.C. Yan, D. Xu, B. Zhang, H.J. Zhang, Q. Yang, and S. Lin, "Graph Embedding and Extensions: A General Framework for Dimensionality Reduction," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, no. 1, pp. 40-51, Jan. 2007. (Pubitemid 46415944)
12. J.N. Hu, W.H. Deng, J. Guo, and W.R. Xu, "Learning a Locality Discriminating Projection for Classification," Knowledge-Based Systems, vol. 22, no. 8, pp. 562-568, 2009.
13. X.J. Zhu and A.B. Goldberg, Introduction to Semi-Supervised Learning. Morgan and Claypool, 2009.
14. H.Y. Zha and Z.Y. Zhang, "Spectral Properties of the Alignment Matrices in Manifold Learning," J. SIAM Rev., vol. 51, no. 3, pp. 545-566, 2009.
15. M. Sugiyama, T. Id, S. Nakajima, and J. Sese, "Semi-Supervised Local Fisher Discriminant Analysis for Dimensionality Reduction," Machine Learning, vol. 78, nos. 1/2, pp. 35-61, 2010.
16. M. Sugiyama, "Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis," J. Machine Learning Research, vol. 8, pp. 1027-1061, 2007. (Pubitemid 46798409)
17. P. Belhumeur, J. Hespanda, and D. Kiregeman, "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)
18. L. Zelnik-Manor and P. Perona, "Self-Tuning Spectral Clustering," Advances in Neural Information Processing Systems 17, vol. 17, pp. 1601-1608, 2005.
19. Z. Jin, J.Y. Yang, Z.S. Hu, and Z. Lou, "Face Recognition Based on the Uncorrelated Discriminant Tranformation," Pattern Recognition, vol. 34, no. 7, pp. 1405-1416, 2001. (Pubitemid 32424906)
20. J. Lu, "Enhanced Locality Sensitive Discriminant Analysis for Image Recognition," Electronics Letters, vol. 46, no. 3, pp. 213-214, 2010.
21. J. Khan, J.S. Wei, M. Ringner, L.H. Saal, M. Ladanyi, and F. Westermann, "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)
22. 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)
23. A. Statnikov, I. Tsamardinos, Y. Dosbayev, and C.F. Aliferis, "GEMS: A System for Automated Cancer Diagnosis and Biomarker Discovery from Microarray Gene Expression Data," Int'l J. Medical Informatics, vol. 74, nos. 7/8, pp. 491-503, 2005. (Pubitemid 41021913)