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Conference Review | Open Access
Advancing Post-Genome Data and System Integration through Machine Learning
Francisco Azuaje
11Department of Computer Science, University of Dublin – Trinity College, Dublin 2, Ireland
Abstract
Research on biological data integration has traditionally focused on the development of systems for the maintenance and interconnection of databases. In the next few years, public and private biotechnology organisations will expand their actions to promote the creation of a post-genome semantic web. It has commonly been accepted that artificial intelligence and data mining techniques may support the interpretation of huge amounts of integrated data. But at the same time, these research disciplines are contributing to the creation of content markup languages and sophisticated programs able to exploit the constraints and preferences of user domains. This paper discusses a number of issues on intelligent systems for the integration of bioinformatic resources.
Copyright
Copyright © 2002 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
