Abstract
The paper presents the technology of gene expression profiles reducing based on the complex use of fuzzy logic methods, statistical criteria and Shannon entropy. Simulation of the reducing process has been performed with the use of gene expression profiles of lung cancer patients. The variance and the average absolute value were changed within the defined range from the minimum to the maximum value, and Shannon entropy from the maximum to the minimum value during the simulation process. 311 gene expression profiles from 7129 were removed as non-informativity during simulation process. The structural block diagram of the step-by-step data processing in order to remove non-informativity gene expression profiles has been proposed as the simulation results.
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Babichev, S., Lytvynenko, V., Gozhyj, A., Korobchynskyi, M., Voronenko, M. (2019). A Fuzzy Model for Gene Expression Profiles Reducing Based on the Complex Use of Statistical Criteria and Shannon Entropy. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education. ICCSEEA 2018. Advances in Intelligent Systems and Computing, vol 754. Springer, Cham. https://doi.org/10.1007/978-3-319-91008-6_55
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