Finding co-clusters of genes and clinical parameters

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn 7 VOLS, Issue , 2005, Pages 906-912

  Yoon, Sungroh ^a,b   Benini, Luca ^a,c   De Micheli, Giovanni ^a,d  

^a IEEE   (United States)

^b Stanford University   (United States)

^c UNIVERSITY OF BOLOGNA   (Italy)

^d EPFL   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

ACUTE MYELOGENOUS LEUKEMIA (AML); CLINICAL PARAMETERS; GENE ONTOLOGY (GO); GENETIC MECHANISMS;

COMPUTATIONAL METHODS; DISEASES; DRUG THERAPY; GENES; GENETIC ENGINEERING; STATISTICAL METHODS;

BIOMEDICAL ENGINEERING;

EID: 33846936834     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. A. V. Aho, J. E. Hopcroft, and J. D. Ullman, Data Structures and Algorithms. Reading, Massachusetts: Addison-Wesley, 1983.
2. E. I. Boyle et al., "GO::TermFinder," Bioinformatics, vol. 20, no. 18, pp. 3710-3715, December 2004.
3. L. Bullinger et al., "Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia," N Engl J Med., vol. 350, no. 16, pp. 1605-1616, April 2004.
4. A. Cignetti, E. Bryant, B. Allione, A. Vitale, R. Foa, and M. A. Cheever, "CD34(+) acute myeloid and lymphoid leukemic blasts can be induced to differentiate into dendritic cells," Blood, vol. 94, pp. 2048-2055, 1999.
5. S. Draghici, Data Analysis Tools for DNA Microarrays. Florida: Chapman & Hall/CRC, 2003.
6. B. D. Harrison, J. A. Adams, M. Briggs, M. L. Brereton, and J. A. L. Yin, "Stimulation of autologous proliferative and cytotoxic T-cell responses by "leukemic dendritic cells" derived from blast cells in acute myeloid leukemia," Blood, vol. 979, pp. 2764-2771, 2001.
7. S. E. Jacobsen, O. P. Veiby, J. Myklebust, C. Okkenhaug, and S. D. Lyman, "Ability of Flt3 ligand to stimulate the in vitro growth of primitive murine hematopoietic progenitors is potently and directly inhibited by transforming growth factor-beta and tumor necrosis factor-alpha," Blood, vol. 87, pp. 5016-5026, 1996.
8. J. Keski-Oja, E. B. Leof, R. M. Lyons, R. J. Coffey Jr, and H. L. Moses, "Transforming growth factors and control of neoplastic cell growth," J Cell Biochem, vol. 33, pp. 95-107, 1987.
9. I. S. Kohane, A. T. Kho, and A. J. Butte, Microarrays for an Integrative Genomics. Cambridge, Massachusetts: The MIT Press, 2003.
10. S. C. Madeira and A. L. Oliveira, "Biclustering algorithms for biological data analysis: A survey," IEEE Transactions on Computational Biology and Bioinformatics, vol. 1, no. 1, pp. 24-45, 2004.
11. E. Riedl, H. Strobl, O. Majdic, and W. Knapp, "TGF-beta 1 promotes in vitro generation of dendritic cells by protecting progenitor cells from apoptosis," J Immunol, vol. 158, pp. 1591-1597, 1997.
12. B. Rosner, Fundamentals of Biostatistics, 5th ed. Pacific Grove, California: Duxbury, 2000.
13. V. G. Tusher, R. Tibshirani, and G. Chu, "Significance analysis of microarrays applied to the ionizing radiation response," Proc. Natl. Acad. Sci USA, vol. 98, no. 9, pp. 5116-5121, April 2001.
14. O. P. Veiby, F. W. Jacobsen, L. Cui, S. D. Lyman, and S. E. Jacobsen, "The Flt3 ligand promotes the survival of primitive hemopoietic progenitor cells with myeloid as well as b lymphoid potential. Suppression of apoptosis and counteraction by TNF-alpha and TGF-beta," J Immunol, vol. 157, pp. 2953-2960, 1996.
15. E. Weisberg et al., "Inhibition of mutant Flt3 receptors in leukemia cells by the small molecule tyrosine kinase inhibitor PKC412," Cancer Cell, vol. 1, pp. 433-443, 2002.
16. M. West et al., "Predicting the clinical status of human breast cancer by using gene expression profiles," Proc Natl Acad Sci USA, vol. 98, no. 20, pp. 11462-11467, September 2001.
17. A. R. Whitney et al., "Individuality and variation in gene expression patterns in human blood," Proc Natl Acad Sci USA, vol. 100, no. 4, pp. 1896-1901, February 2003.
18. S. Yoon, C. Nardini, L. Benini, and G. De Micheli, "Discovering coherent biclusters from gene expression data using zero-suppressed binary decision diagrams," IEEE/ACM Transactions on Computational Biology and Bioinformatics, to appear.