2018
DOI: 10.15587/1729-4061.2018.123634
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Development of a technique for the reconstruction and validation of gene network models based on gene expression profiles

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Cited by 19 publications
(20 citation statements)
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References 19 publications
(23 reference statements)
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“…The analysis of the obtained charts allows us to conclude that the existence of the noise component decreases the degree of the adequacy of the gene networks reconstructed based on the biclusters to the network reconstructed on the basis of complete data. The average of the relative validation criterion for the obtained models of gene networks are significantly less than the appropriate value of this criterion in the case of gene networks reconstruction based on the gene expression profiles without noise [30]. Moreover, the analysis of the charts in Figure 12 has shown that the increase of the noise level in the data decreases the average of the relative validation criterion.…”
Section: Results Of the Simulation With The Use Of Objective Clusterimentioning
confidence: 95%
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“…The analysis of the obtained charts allows us to conclude that the existence of the noise component decreases the degree of the adequacy of the gene networks reconstructed based on the biclusters to the network reconstructed on the basis of complete data. The average of the relative validation criterion for the obtained models of gene networks are significantly less than the appropriate value of this criterion in the case of gene networks reconstruction based on the gene expression profiles without noise [30]. Moreover, the analysis of the charts in Figure 12 has shown that the increase of the noise level in the data decreases the average of the relative validation criterion.…”
Section: Results Of the Simulation With The Use Of Objective Clusterimentioning
confidence: 95%
“…Ten largest biclusters from each of the studied data were selected for the further analysis. Reconstruction of the gene regulatory networks and validation of the obtained models were performed based on Cytoscape software with the use of correlation inference algorithm [26].Detailed description of the used information technology for the reconstruction and validation of gene networks is presented in [30]. Figures 8-11 presents the charts of general Harrington desirability index versus the value of thresholding coefficient for both the data without noise and data with different levels of noise component.…”
Section: Results Of the Simulation With The Use Of Objective Clusterimentioning
confidence: 99%
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“…An option to overcome such difficulties may be the use of neural algorithms. This approach is used in papers [10,11]. However, even in this case, the derivation of the parametric description of a complex system in the analytical form was not considered.…”
Section: запропонований метод структурного функцIонально-вартiсного мmentioning
confidence: 99%
“…The optimal wavelet and the level of wavelet decomposition are determined based on the maximum value of the Shannon entropy for the allocated noise component and the thresholding coefficient optimal value is determined based on the minimum value of the Shannon entropy for filtered data within the framework of the proposed technology. The proposed by the authors technology was successfully implemented for the gene expression profiles filtering within the framework of the information technology of gene expression profiles processing for the purpose of gene regulatory networks reconstruction [29,30]. In this paper we propose the model of the wavelet filter optimal parameters determination based on the use of ratio of the Shannon entropies for the filtered signal and the allocated noise component.…”
Section: Empirical Mode Decomposition and Discrete Wavelet Transformmentioning
confidence: 99%