Biopolym. Cell. 2016; 32(1):70-79.
http://dx.doi.org/10.7124/bc.00090F
Bioinformatics
Computational analysis of microarray gene expression profiles of lung cancer
1Babichev S. A., 2Kornelyuk A. I., 3Lytvynenko V. I., 4Osypenko V. V.
  1. University of J. E. Purkyně in Ústí nad Labem
    1, Pasteur Str, Ústí nad Labem, Czech Republic, 400 96
  2. Institute of Molecular Biology and Genetics, NAS of Ukraine
    150, Akademika Zabolotnoho Str., Kyiv, Ukraine, 03680
  3. Kherson National Technical University
    24, Beryslavske sh, Kherson, Ukraine, 73008
  4. National University of Life and Environmental Sciences of Ukraine
    15, Heroyiv Oborony Str., Kyiv, Ukraine, 03041

Abstract

Aim. The article presents the researches on the optimization of the DNA microarray data processing, which is aimed at improving the quality of object clustering. Methods. Data preprocessing was performed with program R using Bioconductor package. Modelling the clustering process was made in the software environment KNIME using the program WEKA functions. Results. The data preprocessing is shown to be optimal while using such techniques as the background correction rma method, quantile normalization, mas PM correction and summarization by mas method. The simulation results have demonstrated a high effectiveness of the clustering algorithm Sota for this category of data. Conclusion. The results of the research have shown that improving the quality of biological object clustering is possible by means of hybridization and optimization of the methods and algorithms at different stages of data processing.
Keywords: clustering, gene expression, data preprocessing, DNA microchip
Full text: (PDF, in English)

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