Data-driven theory refinement algorithms for bioinformatics
نویسندگان
چکیده
Bioinformatics and related applications call for e cient algorithms for knowledge intensive learning and data driven knowledge re nement Knowledge based arti cial neural networks o er an attractive approach to ex tending or modifying incomplete knowledge bases or do main theories We present results of experiments with sev eral such algorithms for data driven knowledge discovery and theory re nement in some simple bioinformatics appli cations Results of experiments on the ribosome binding site and promoter site identi cation problems indicate that the performance of KBDistAl and Tiling Pyramid algorithms com pares quite favorably with those of substantially more com putationally demanding techniques
منابع مشابه
Data-Driven Theory Refinement Algorithms for Bloinformatics - Neural Networks, 1999. IJCNN '99. International Joint Conference on
Bioinformatics and related applications call for efficient algorithms for knowledgeintensive learning and data-driven knowledge refinement. Knowledge based artitending or modifying incomplete knowledge bases or domain theories. we present results of experiments with several such algorithms for data-driven knowledge discovery and theory refinement in some simple bioinformatics applications. Resu...
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| Bioinformatics and related applications call for eecient algorithms for knowledge-intensive learning and data-driven knowledge reenement. Knowledge based arti-cial neural networks ooer an attractive approach to extending or modifying incomplete knowledge bases or domain theories. We present results of experiments with several such algorithms for data-driven knowledge discovery and theory reen...
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