The paper presents the results of the research concerning the development of the hybrid model of 1-D signal adaptive filter based on the complex use of both the empirical mode decomposition and the wavelet analysis. Implementation of the proposed model involves three stages. Firstly, the initial signal is decomposed to the empirical modes by the Huang transform with allocation the components, which contain the noise. Then the wavelet filtering is performed to remove the noise component. The optimal parameters of the wavelet filter are determined based on the minimal value of ratio of Shannon entropy for the filtered data and the allocated noise component and these parameters are determined depending on type of the studied component of the signal. Finally, the signal is reconstructed with the use of the processed modes. The results of the simulation with the use of the test data have shown higher effectiveness of the proposed method in comparison with standard method of the signal denoising based on wavelet analysis.

The paper presents the research results concerning an effectiveness evaluation of information technology of gene expression profiles processing for purpose of gene regulatory networks reconstruction. The information technology is presented as a structural block-chart of step-by-step stages of the studied data processing. The DNA microchips of patients, who were investigated on different types of cancer, were used as experimental data. The optimal parameters of data processing algorithm at appropriate stage of this process implementation by quantity criteria of data processing quality were determined during simulation. Validation of the reconstructed gene networks was performed with the use of ROC-analysis by comparison of character of genes interconnection in both the basic network and networks reconstructed based on the obtained biclusters.

The paper presents the technology of gene expression profiles filtering based on the wavelet analysis methods. A structural block-chart of the wavelet-filtering process, which involves concurrent calculation of Shannon entropy for both the filtered data and allocated noise component is proposed. Simulation of the wavelet-filtering process was performed with the use of orthogonal and biorthogonal wavelets on different levels of wavelet decomposition and with the use of various values of the thresholding coefficient. Result of the simulation has allowed us to propose the technology to determine the optimal parameters of the wavelet filter based on complex analysis of the filtered data and allocated noise component.