ACM Home Page
Please provide us with feedback. Feedback
The emerging role of biogrids
Full text HtmlHtml (24 KB),  PdfPdf (259 KB)
Source
Communications of the ACM archive
Volume 47 ,  Issue 11  (November 2004) table of contents
Bioinformatics
SPECIAL ISSUE: Bioinformatics: transforming biomedical research and medical care table of contents
Pages: 52 - 57  
Year of Publication: 2004
ISSN:0001-0782
Authors
Mark Ellisman
Michael Brady  Oxford University in the U.K
David Hart  Indiana University
Fang-Pang Lin  National Center for High-Performance Computing in Hsinchu, Taiwan
Matthias Müller  High Performance Computing Center Stuttgart in Germany.
Larry Smarr  University of California, San Diego
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 1,   Downloads (12 Months): 70,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1029496.1029526
What is a DOI?

ABSTRACT

Four biomedically oriented grid systems, ranging from SARS diagnosis to arthropod evolution, demonstrate the promise of grid computing in medical practice and biological science.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
Birchard, K. Online system to allow easy access to mammograms. Medical Post 38, 40 (Nov. 5, 2002); www.medicalpost.com/mpcontent/ article.jsp?content=/content/EXTRACT/RAWART/3840/51B.html.
 
3
DeFanti, T., Foster, I., Papka, M., Stevens, R., and Kuhfuss, T. Overview of the I-WAY: Wide-area visual supercomputing. Int. J. Supercomput. Applic. 10, 2 (Summer/Fall 1996), 123--130.
 
4
Ellisman, M. and Peltier, S. Medical data federation: The biomedical informatics research network. In The Grid: Blueprint for a New Computing Infrastructure, 2nd Ed., I. Foster and C. Kesselman, Eds. Morgan Kaufmann, San Francisco, 2004.
 
5
Felsenstein, J. Evolutionary trees from DNA sequences: A maximum likelihood approach. J. Mol. Evol. 17 (1981), 368--376.
 
6
 
7
Keller, R., Krammer, B., Müller, M., Resch, M., and Gabriel, E. Towards efficient execution of MPI applications on the grid: Porting and optimization issues. J. Grid Comput. 1, 2 (2003), 133--149.
 
8
Olsen, G., Matsuda, H., Hagstrom, R., and Overbeek, R. fastDNAml: A tool for construction of phylogenetic trees of DNA sequences using maximum likelihood. Comput. Appl. Biosci. 10 (Feb. 1994), 41--48.
 
9
Rantzau, D., Frank, K., Lang, U., Rainer, D., and Wossner, U. COVISE in the CUBE: An environment for analyzing large and complex simulation data. In Proceedings of the Second Workshop on Immersive Projection Technology (Ames, IA, May 11--12). Iowa Center for Emerging Manufacturing Technology, Ames, IA, 1998.
10

Collaborative Colleagues:
Mark Ellisman: colleagues
Michael Brady: colleagues
David Hart: colleagues
Fang-Pang Lin: colleagues
Matthias Müller: colleagues
Larry Smarr: colleagues