Expert Systems
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Sequence similarity searching is commonly used to help clarify the biochemical and physiological features of newly discovered genes or proteins. An efficient similarity search relies on the choice of tools and their associated subprograms and numerous parameter settings. This could be very challenging for similarity search users, especially those at the beginner level. To assist researchers in selecting optimal search programs and parameter settings for efficient sequence similarity searches, we have developed a Web-based expert system, Smart Sequence Similarity Search (S4). The system is implemented in Java and Jess scripts, and uses the Jess Expert System as its reasoning core. The expert knowledge provided for a sequence similarity search is represented in the form of decision tree and stored in a XML file. The system also provides interfaces for expert users to improve this knowledge by extending the decision tree. With its capability to continuously improve sequence similarity searches through a decision tree, the Web-based expert system provides a solid advising tool for researchers interested in efficient sequence similarity searches.