A multi-metric similarity based analysis of microarray data

Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007

Volumn , Issue , 2007, Pages 317-324

  Altiparmak, Fatih ^a   Erdal, Selnur ^b   Ozturk, Ozgur ^a   Ferhatosmanoglu, Hakan ^a  

^a OHIO STATE UNIVERSITY   (United States)

^b THE OHIO STATE UNIVERSITY WEXNER MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CASE STUDIES; CLUSTERING METHODS; CO-OCCURRENCE; DATA SETS; DISTANCE METRIC; DISTANCE METRICS; FUNCTIONAL RELATIONSHIPS; INTERNATIONAL CONFERENCES; MICROARRAY DATA; MICROARRAY DATABASES; MICROARRAY DATASETS; NEGATIVE CORRELATIONS; STANFORD; YEAST CELL CYCLES;

BIOCOMMUNICATIONS; BIOINFORMATICS; CHLORINE COMPOUNDS; CLUSTER ANALYSIS; DATA REDUCTION; FLOW OF SOLIDS; INFORMATION SCIENCE;

GENES;

EID: 49049117812     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIBM.2007.26     Document Type: Conference Paper

References (21)

1. J. Aach and G.M. Church, Aligning gene expression time series with time warping algorithms, Bioinformatics 17(6) (2001), :495-508.
2. C.A. Ball and et al, The stanford microarray database accommodates additional microarray platforms and data formats, Nucleic Acids Res 33(1) (2005), 580-582.
3. M.P.S. Brown and et al., Knowledge-based analysis of microarray gene expression data by using support vector machines, Proceedings of the National Academy of Sciences. 1 (97), 262-267.
4. R. O. Duda and P. E. Hart, Pattern classification and scene analysis, Wiley, New York, NY, 1973.
5. S. Erdal, O. Ozturk, D. Armbruster, H. Ferhatosmanoglu, and W. Ray, A time series analysis of microarray data., BIBE'04 (2004), 366-378.
6. E.W. Forgy, Cluster analysis of multivariate data: Efficiency versus interpretability of classifications, Biometrics 21 (1965), 768.
7. T. Furey, N. Cristianini, N. Duffy, D. Bednarski, M. Schummer, and D. Haussler, Support vector machine classification and validation of cancer tissue samples using microarray expressioin data, Bioinformatics 16(10) (Oct 2000), 906-14.
8. F.D. Gibbons and F.P. Roth, Judging the quality of gene expression-based clustering methods using gene annotation., Genome Res. 12(10) (2002 Oct), 1574-81.
9. C.J. Jeffery, Moonlighting proteins, Trends Biochem. Sci. 24 (1999), 8-11.
10. J. Kimmelman and et al, Activating phosphorylation of the kin28p subunit of yeast tfiih by cak1p, Molecular and Cellular Biology 19(7) (1999), 47744787.
11. T. Kohnen, Self-organized formation of topologically correct feature maps, Biological Cybernetics 43 (1982), 59-69.
12. H.K. Lee, A.K. Hsu, J. Sajdak, J. Qin, and P. Pavlidis, Co-expression analysis of human genes across many microarray data sets, Genome Res. 14 (2004), 10851094.
13. S. L. Ooi, D. D. Shoemaker, and J. D. Boeke, Dna helicase gene interaction network defined using synthetic lethality analyzed by microarray, Nature Genetics 35 (2003), 277-286.
14. W.J. Rui, Regulation of eukaryotic dna replication and nuclear structure, Cell Research 9 (1999), no. 3, 163-170.
15. H. Sakoe and S. Chiba, Dynamic programming algorithm optimization for spoken word recognition., IEEE Trans. Acustics, Speech and Signal Processing 26(1) (1978).
16. L. Todorovski, B. Cestnik, and M. Kline, Qualitative clustering of short time series: a case study of firms reputation data, Conference on Data Mining and Warehouses (SIKDD 2002).
17. O.G. Troyanskaya, K. Dolinski, A.B. Owen, R.B. Altman, and D. Botstein, A bayesian framework for combining heterogeneous data sources for gene function prediction (in s. cerevisiae), Proc Natl Acad Sci USA 100(14) (2003), 8348-53.
18. M. G. Walker, Introduction to statistics for bioinformatics, with applications to expression microarrays, CSB Tutorial sessions (2003).
19. C-C Wu, Statistical analysis of parameters of yeast (saccharomyces cerevisiae) cell cycle regulated genes, (2004).
20. L.F. Wu and et al., Large-scale prediction of saccharomyces cerevisiae gene function usingoverlapping transcriptional clusters, Nature Genet. 31 (2002), 255-265.
21. Y-C Yang and et al, Genetic/genomic analysis of signal transduction pathways using cdna microarray technology, Nature Genetics 23 (1999), supplement p 34.