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Beyond Interoperability - Tracking and Managing the Results of Computational Applications.

Judith Bayard Cushing, Justin Laird, Emir Pasalic, Elizabeth Kutter, Tim Hunkapiller, Frank Zucker, David P. Yee: Beyond Interoperability - Tracking and Managing the Results of Computational Applications. SSDBM 1997: 223-236
@inproceedings{DBLP:conf/ssdbm/CushingLPSK97,
  author    = {Judith Bayard Cushing and
               Justin Laird and
               Emir Pasalic and
               Elizabeth Kutter and
               Tim Hunkapiller and
               Frank Zucker and
               David P. Yee},
  editor    = {Yannis E. Ioannidis and
               David M. Hansen},
  title     = {Beyond Interoperability - Tracking and Managing the Results of
               Computational Applications},
  booktitle = {Ninth International Conference on Scientific and Statistical
               Database Management, Proceedings, August 11-13, 1997, Olympia,
               Washington, USA},
  publisher = {IEEE Computer Society},
  year      = {1997},
  isbn      = {0-8186-7952-2},
  pages     = {223-236},
  ee        = {db/conf/ssdbm/CushingLPSK97.html},
  crossref  = {DBLP:conf/ssdbm/97},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

Molecular biology applications, like those of other scientific domains, need to store and view large amounts of specialized quantitative information. With the advent of high speed sequencing technology and considerable funding to ``map" the genomes of key biological organisms, public databases such as GenBank, PDB, EMBL, JIPID, and SwissProt make millions of genetic sequences available to molecular biologists, and industry and university laboratories maintain large databases. The need for common interfaces and query languages to exploit these heterogeneous databases is well documented, and several such systems now exist or are under development. Our own work on database and program interoperability in this domain has shown, however, that providing an interface is but a first step towards making these databases fully useful.

The system we are developing integrates and tracks inputs and results from numerous computational biology programs. It helps researchers organize result items from sequence comparisons into ``clusters" that can be marked, named, annotated, and manipulated. An alpha version is implemented in Smalltalk.

This paper describes the scientific problem our system aims to solve, as well as current barriers to development and research opportunities suggested by those barriers. We present its conceptual data model, the current prototype, and future implementation plans.

Copyright © 1997 by The Institute of Electrical and Electronic Engineers, Inc. (IEEE). Abstract used with permission.

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Yannis E. Ioannidis, David M. Hansen (Eds.): Ninth International Conference on Scientific and Statistical Database Management, Proceedings, August 11-13, 1997, Olympia, Washington, USA. IEEE Computer Society 1997, ISBN 0-8186-7952-2
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