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Research Problems in Genome Databases.

Nathan Goodman: Research Problems in Genome Databases. PODS 1995: 125
@inproceedings{DBLP:conf/pods/Goodman95,
  author    = {Nathan Goodman},
  title     = {Research Problems in Genome Databases},
  booktitle = {Proceedings of the Fourteenth ACM SIGACT-SIGMOD-SIGART Symposium
               on Principles of Database Systems, May 22-25, 1995, San Jose,
               California},
  publisher = {ACM Press},
  year      = {1995},
  isbn      = {0-89791-730-8},
  pages     = {125},
  ee        = {http://doi.acm.org/10.1145/212433.220202, db/conf/pods/Goodman95.html},
  crossref  = {DBLP:conf/pods/95},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

The Human Genome Project is a fifteen year, international project that seeks to identify all of the genes in the human genome, and to eventually sequence the 3 billion bases of DNA that comprise the human genome. The Human Genome Project is a fascinating scientific adventure and raises exciting research challenges for computer science. This seminar will present several kinds of database challenges that arise.

1. Laboratory databases have to keep track of tens to hundreds of thousands of samples as they flow through complex, multi-step procedures. To make matters worse, these procedures change frequently as new lab techniques are introduced, and the database must evolve to keep pace.

2. There is a need for databases to keep track of the results produced by genome labs, which are often complex structures such as maps, and sequences.

3. There is a need for databases that integrate results from multiple labs.

4. A great deal of genomic data is descriptive in nature and is best represented as free text. There is a need to integrate text databases with more traditional databases.

5. An increasing amount of genomic data is visual in nature, leading to a need for image databases.

6. Scientific results generally consist of (i) data, and (ii) an interpretation of the data in light of current theory. In most genome databases, the data and results are explicit, but the underlying theory is implicit. Since theories change from time-to-time, we are left with the very big problem of reinterpretting old data in a new light.

Copyright © 1995 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.


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Proceedings of the Fourteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, May 22-25, 1995, San Jose, California. ACM Press 1995, ISBN 0-89791-730-8
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Referenced by

  1. Anthony J. Bonner, Giansalvatore Mecca: Querying String Databases with Transducers. DBPL 1997: 118-135
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