Biology Reference
In-Depth Information
[9]
U. Feige, S. Goldwasser, L. Lovasz, S. Safra, and M. Szegedy. Approximating the
maximum clique is almost NP -complete. In IEEE Symposium on the Foundations
of Computer Science , pages 2-12, 1991.
[10]
U. Feige, D. Peleg, and G. Kortsarz. The dense k-subgraph problem. Algorithmica ,
29:410-421, 2001.
[11]
M. R. Fellows and M. A. Langston. Nonconstructive tools for proving polynomial-
time decidability. Journal of the ACM , 35:727-739, 1988.
[12]
M. R. Fellows and M. A. Langston. On search, decision, and the efficiency of
polynomial-time algorithms. Journal of Computer and Systems Sciences , 49:769-
779, 1994.
[13]
I. C. Gerling, C. Ali, and N. Lenchik. Characterization of early developments in the
splenic leukocyte transcriptome of NOD mice. Ann N Y Acad Sci , 1005:157-160,
2003.
[14]
I. C. Gerling, S. Singh, N. I. Lenchik, D. R. Marshall, and J. Wu. New data analy-
sis and mining approaches identify unique proteome and transcriptome markers of
susceptibility to autoimmune diabetes. Mol Cell Proteomics , 5(2):293-305, 2006.
[15]
R. Ihaka and R. Gentleman. R: A language for data analysis and graphics. Journal of
Computational and Graphical Statistics , 5:299-314, 1996.
[16]
R. Kirova, M. A. Langston, X. Peng, A. D. Perkins, and E. J. Chesler. A systems
genetic analysis of chronic fatigue syndrome: combinatorial data integration from
snps to differential diagnosis of disease. In International Conference for the Critical
Assessment of Microarray Data Analysis (CAMDA) , 2006.
[17]
H. Kitano. Computational systems biology. Nature , 420(6912):206-210, 2002.
[18]
H. Kitano. Systems biology: a brief overview. Science , 295(5560):1662-1664, 2002.
[19]
M. A. Langston, L. Lan, X. Peng, N. E. Baldwin, C. T. Symons, B. Zhang, and
J. R. Snoddy. A combinatorial approach to the analysis of differential gene expres-
sion data: the use of graph algorithms for disease prediction and screening. In K. F.
Johnson and S. M. Lin, editors, Methods of Microarray Data Analysis IV, Papers from
CAMDA '03 , pages 223-238. Kluwer Academic Publishers, 2005.
[20]
M. A. Langston, A. D. Perkins, A. M. Saxton, J. A. Scharff, and B. H. Voy. Innova-
tive computational methods for transcriptomic data analysis. In ACM Symposium on
Applied Computing , 2006.
[21]
E. Pennisi. Systems biology. tracing life's circuitry. Science , 302(5651):1646-1649,
2003.
[22]
I. Seefeldt, G. Nebrich, I. Romer, L. Mao, and J. Klose. Evaluation of 2-de protein
patterns from pre- and postnatal stages of the mouse brain. Proteomics , 6(18):4932-
4939, 2006.
[23]
J. C. Setubal and J. Meidanis. Introduction to Computational Molecular BIology .
PWS Publishing Company, 1997.
[24]
L. Shi, L. H. Reid, W. D. Jones, R. Shippy, J. A. Warrington, S. C. Baker, P. J.
Collins, F. de Longueville, E. S. Kawasaki, K. Y. Lee, Y. Luo, Y. A. Sun, J. M.
Willey, R. A. Setterquist, G. M. Fischer, W. Tong, Y. P. Dragan, D. J. Dix, F. W.
Frueh, F. M Goodsaid, D. Herman, R. V. Jensen, C. D. Johnson, E. K. Lobenhofer,
R. K. Puri, U. Schrf, J. Thierry-Mieg, C. Wang, M. Wilson, P. K. Wolber, L. Zhang,
W. Slikker, L. Shi, L. H. Reid, and M. A. Q. C. Consortium. The microarray quality
control (maqc) project shows inter- and intraplatform reproducibility of gene expres-
Search WWH ::




Custom Search