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Volume 40, Number 2, 2001
Deep computing for the life sciences
 Table of contents: arrowHTML arrowPDF arrowASCII   This article: arrowHTML arrowPDF arrowASCII arrowCopyright info
   

DiscoveryLink: A system for integrated access to life sciences data sources - References
by L. M. Haas, P. M. Schwarz, P. Kodali, E. Kotlar, J. E. Rice, and W. C. Swope

Cited references and notes

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  25. Actually, the optimizer normally ignores pairs when there is no predicate connecting them (e.g., Compounds and Proteins in this query), because typically these “cross-products” do not make good plans.
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  27. The host variable :KETANSERIN_MOL is presumed to contain an appropriate representation of the ketanserin structure, perhaps as generated by a sketching tool.
  28. In this paper, we represent query fragments in SQL; the actual wrapper interface will use an equivalent data structure that does not require parsing by the wrapper.
  29. M. Tork Roth, F. Ozcan, and L. Haas, “Cost Models DO Matter: Providing Cost Information for Diverse Data Sources in a Federated System,” Proceedings of the Conference on Very Large Data Bases (VLDB), Edinburgh, Scotland, September 1999, ACM, New York (1999).
  30. We did not analyze why this occurred, because it was not unexpected: our experience with DataJoiner over the years is that it usually introduces little overhead, and occasionally can run a transaction faster than the native data source. There are several possible reasons why this script might run faster through DiscoveryLink, among them, DiscoveryLink's superior optimizer and the fact that it ran on a separate machine, hence could apply more hardware to the problem. In this instance, the result is probably due to the DiscoveryLink engine exploiting the resources of its separate machine, because the four queries in script four are fairly simple, and with one exception leave little room for optimization.
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  48. See http://www.netgenics.com/.
  49. See http://www.tripos.com.
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  55. See http://www.oracle.com/.
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