Mining coherent gene clusters from gene-sample-time microarray data

KDD-2004 - Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2004, Pages 430-439

  Jiang, Daxin ^a   Pei, Jian ^a,b   Ramanathan, Murali ^a   Tang, Chun ^a   Zhang, Aidong ^a  

^a UNIVERSITY AT BUFFALO   (United States)

^b SIMON FRASER UNIVERSITY   (Canada)

Author keywords

Bioinformatics; Clustering; Microarray data

Indexed keywords

ALGORITHMS; BIOMEDICAL ENGINEERING; DISEASES; ENGINEERING RESEARCH; GENES; MATRIX ALGEBRA; MEDICAL APPLICATIONS; PATTERN RECOGNITION; TIME SERIES ANALYSIS;

BIOINFORMATICS; CLUSTERING; COHERENT GENE CLUSTERS; MIRCOARRAY DATA;

DATA MINING;

EID: 12244250138     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1014052.1014101     Document Type: Conference Paper

References (22)

1. Alizadeh A.A., et al. Distinct types of diffuse large b-cell lymphoma identified by gene expression profiling. Nature, Vol.403:503-511, February 2000.
2. Alon U., et al. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide array. Proc. Natl. Acad. Sci. USA, Vol. 96(12):6745-6750, June 1999.
3. Black M.A. and Doerge R.W. Calculation of the minimum number of replicate spots required for detection of significant gene expression fold change in microarray experiments Bioinformatics, 18:1609-1616, 2002
4. Ben-Dor A., et al. Class discovery in gene expression data. In Proc. Fifth Annual Inter. Conf. on Computational Molecular Biology (RECOMB 2001).
5. Kerr M.K. and Churchill G.A. Bootstrapping cluster analysis: Assessing the reliability of conclusions from microarray experiments. Proc. Natl. Acad. Sci. USA, Vol. 98:8961-8965.
6. Cheng Y. and Church G.M. Biclustering of expression data. Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology (ISMB), 2000.
7. Golub T.R., et al. Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science, Vol. 286(15):531-537, October 1999.
8. Jiang D., et al. Interactive Exploration of Coherent Patterns in Time-Series Gene Expression Data. In KDD'03.
9. Moler E.J., et al. Analysis of Molecular Profile Data Using Generative and Discriminative Methods. Physiological Genomics, Vol. 4(2):109-126, 2000.
10. Pel J., et al. CLOSET: An efficient algorithm for mining frequent closed itemsets. In DMKD'00.
11. Pei J., et al. MaPle: A Fast Algorithm for Maximal Pattern-based Clusterin. In IEEE ICDM'03.
12. Herwig R., et al. Large-Scale Clustering of cDNA-Fingerprinting Data. Genome Research, 9:1093-1105, 1999.
13. Rymon R. Search through systematic set enumeration. In Proc. 1992 Int. Conf. Principle of Knowledge Representation and Reasoning (KR'92).
14. Dudoit S., et al. Comparison of discrimination methods for the classification of tumors using gene expression data. J. of the American Statistical Association, Vol. 97, No. 457.
15. Tamayo P., et al. Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. Proc. Natl. Acad. Sci. USA, Vol. 96(6):2907-2912, March 1999.
16. Tang C., et al. Mining phenotypes and informative genes from gene expression data. In SIGKDD'03.
17. Tavazoie S., et al. Systematic determination of genetic network architecture. Nature Genet, pages 281-285, 1999.
18. Tusher V.G., et al. Significance Analysis of Microarrays Applied to the Ionizing Radiation Response. Proc. Natl. Acad. Sci. USA, Vol. 98(9):5116-5121, April 2001.
19. Wang H., et al. Clustering by Pattern Similarity in Large Data Sets. In SIGMOD 2002.
20. Weinstock-Guttman B., et al., Genomic effects of interferon-b in multiple sclerosis patients. Accepted pending revisions Journal of Immunology, 2003.
21. Xing E.P. and Karp R.M. Cliff: Clustering of high-dimensional microarray data via iterative feature filtering using normalized cuts. Bioinformatics, Vol. 17(1):306-315, 2001.
22. Yang J., et al. δ-cluster: Capturing Subspace Correlation in a Large Data Set. In ICDE 2002.