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ANNODA: tool for integrating molecular-biological annotation data

Prompramote, Supawan and Chen, Yi-Ping Phoebe 2005, ANNODA: tool for integrating molecular-biological annotation data, in 21st International Conference on Data Engineering workshops, 2005, IEEE Xplore, Piscataway, N.J., pp. 1166-1174.

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Title ANNODA: tool for integrating molecular-biological annotation data
Author(s) Prompramote, Supawan
Chen, Yi-Ping Phoebe
Conference name International Conference on Data Engineering (21st : 2005 : Tokyo, Japan)
Conference location Tokyo, Japan
Conference dates 3-4 April 2005
Title of proceedings 21st International Conference on Data Engineering workshops, 2005
Editor(s) Zaki, M.
Publication date 2005
Conference series International Conference on Data Engineering
Start page 1166
End page 1174
Publisher IEEE Xplore
Place of publication Piscataway, N.J.
Summary Collecting, analyzing, and making Molecularbiological annotation data accessible in different public data sources is still an ongoing project. Integration of such data from these data sources might lead to valuable biological knowledge. There are numerous annotation data and only some of those are structured. The number and contents of related sources are continuously increasing. In addition, the existing data sources have their own storage structure and implementation. As a result, these could lead to a limitation in the combining of annotation. Here, we proposed a tool, called ANNODA, for integrating Molecular-biological annotation data. Unlike the past work on database interoperation in the bioinformatics community, this database design uses web-links which are very useful for interactive navigation and meanwhile it also supports automated large-scale analysis tasks.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 0769526578
9780769526577
Language eng
Field of Research 080199 Artificial Intelligence and Image Processing not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2005 IEEE.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30005726

Document type: Conference Paper
Collections: School of Information Technology
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