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- W2103292077 abstract "Recently, too much data is being produced in every field of our life. Especially in science, large amounts of data are needed to analyze in order to reveal valuable knowledge hidden in raw data. The number of DNA sequences has been growing fast since the beginning of the Human Genome Program (HGP) so it becomes increasingly important to automate the identification of functional elements in DNA. But human analysts with the traditional tools can no longer make sense. In this study, we employ data mining techniques including ANN, ANFIS and newly developed algorithms ke-REM and IREM to extract diamonds of knowledge from DNA sequences and evaluate their performances." @default.
- W2103292077 created "2016-06-24" @default.
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- W2103292077 date "2014-01-01" @default.
- W2103292077 modified "2023-09-25" @default.
- W2103292077 title "Computational Approach for Promoter Identification with data Mining Techniques" @default.
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- W2103292077 doi "https://doi.org/10.9790/3021-04173141" @default.
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