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Here, we extend non-scalar attribute management in fuzzy queries with the use of ontologies.
Nowadays there are many proposals that allow users to perform fuzzy queries on relational databases.
The use of a lexical analyser that can for example handle fuzzy queries and replace synonyms can make the search for users more intuitive and flexible.
This framework allows users to input any fuzzy queries, is capable of measuring the results quantitatively, and performs well in retrieving assemblies with specified characteristics.
In the relational setting, extensions of the relational algebra as well as of SQL-like languages have been proposed and a wide range of fuzzy queries has been made available.
Regardless of these proposals, fuzzy queries are really useful on scalar values where fuzzy sets can be adjusted to the user needs and domains, but non-scalar values are a more complex task.
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In addition, we have developed a fuzzy query method to predict protein stability with partial information.
With a fuzzy query interface to input subjective and objective factors, users can determine the most suitable web service for personal use.
We have developed a web server for predicting the protein stability changes upon single mutations by using fuzzy query mechanism and it is available at http://bioinformatics.myweb.hinet.net/fqstab.htm.net/fqstab.htm
In addition to the general necessity of data profiling (developing a statistical knowledge of each variable's properties), fuzzy query capabilities give analysts and engineers, a highly flexible and robust method of semantically scouring large databases for new relationships, as well as for studying the degree to which known behaviors and relationships exist and can be isolated.
Depending on the respective focus of data mining, a precise query for identifiers and a fuzzy query for keywords of functional annotations were designed for automated data retrieval of tandem duplicated gene clusters and flexible functional annotations.
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