Computational intelligence techniques for acute leukemia gene expression data classification
暂无分享,去创建一个
[1] J. A. Hartigan,et al. A k-means clustering algorithm , 1979 .
[2] J. Barker,et al. Large-scale temporal gene expression mapping of central nervous system development. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[3] Kuldip K. Paliwal,et al. Fast K-dimensional tree algorithms for nearest neighbor search with application to vector quantization encoding , 1992, IEEE Trans. Signal Process..
[4] Aidong Zhang,et al. Cluster analysis for gene expression data: a survey , 2004, IEEE Transactions on Knowledge and Data Engineering.
[5] Bernard Chazelle,et al. Filtering search: A new approach to query-answering , 1983, 24th Annual Symposium on Foundations of Computer Science (sfcs 1983).
[6] Dimitrios Gunopulos,et al. Automatic subspace clustering of high dimensional data for data mining applications , 1998, SIGMOD '98.
[7] D. Signorini,et al. Neural networks , 1995, The Lancet.
[8] Roded Sharan,et al. CLICK: A Clustering Algorithm for Gene Expression Analysis , 2000, ISMB 2000.
[9] James C. Bezdek,et al. Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.
[10] G. Church,et al. Systematic determination of genetic network architecture , 1999, Nature Genetics.
[11] Dimitris K. Tasoulis,et al. Unsupervised Clustering of Bioinformatics Data , 2004 .
[12] Chris H. Q. Ding,et al. Analysis of gene expression profiles: class discovery and leaf ordering , 2002, RECOMB '02.
[13] Dimitris K. Tasoulis,et al. UNSUPERVISED CLUSTER ANALYSIS IN BIOINFORMATICS , 2004 .
[14] J. Mesirov,et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.
[15] Franco P. Preparata,et al. Sequencing-by-hybridization revisited: the analog-spectrum proposal , 2004, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[16] J. Thomas,et al. An efficient and robust statistical modeling approach to discover differentially expressed genes using genomic expression profiles. , 2001, Genome research.
[17] George D. Magoulas,et al. Hybrid methods using evolutionary algorithms for on-line training , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).
[18] Ron Kohavi,et al. Irrelevant Features and the Subset Selection Problem , 1994, ICML.
[19] Luis Mateus Rocha,et al. Singular value decomposition and principal component analysis , 2003 .
[20] Philip S. Yu,et al. Fast algorithms for projected clustering , 1999, SIGMOD '99.
[21] D. Botstein,et al. Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[22] Michael N. Vrahatis,et al. The New k-Windows Algorithm for Improving the k-Means Clustering Algorithm , 2002, J. Complex..
[23] Richard S. Sutton,et al. Online Learning with Random Representations , 1993, ICML.
[24] U. Alon,et al. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. , 1999, Proceedings of the National Academy of Sciences of the United States of America.
[25] Hermann A. Maurer,et al. Efficient worst-case data structures for range searching , 1978, Acta Informatica.
[26] Richard M. Karp,et al. CLIFF: clustering of high-dimensional microarray data via iterative feature filtering using normalized cuts , 2001, ISMB.