Information Technology of Gene Expression Profiles Processing for Purpose of Gene Regulatory Networks Reconstruction

Abstract

The paper presents the information technology of gene expression profiles processing in order to reconstruct gene regulatory networks. The information technology is presented as a structural block-chart, which contains all stages of studied data processing. DNA microchips of patients, which were studied on different types of diseases, were used as experimental data. The relative criteria of validation for all reconstructed networks were calculated during simulation process. The obtained results show high efficiency of the proposed technology. High values of the validation criteria indicate a high level of the obtained gene networks objectivity.

An Evaluation of Information Technology of Gene Expression Profiles Processing Stability for Different Levels of Noise Component

“…The structural block-chart of the information technology of gene expression profiles processing for purpose of the gene regulatory networks reconstruction and validation of the obtained models is presented in Figure 1 [14]. The implementation of this technology involves the following stages:…”

“…However, it should be noted that the main disadvantages of this technology direct implementation are the large quantity of small biclusters and large amount of useful information loss at the stage of biclusters formation. In [14] authors proposed the information technology of step by step gene expression profiles processing in order to reconstruct gene regulatory networks. Practical implementation of this technology involves gene expression profiles clustering with the use of DBSCAN clustering algorithm [15] at the first step and SOTA clustering algorithm [16,17] at the second step.…”

A Hybrid Model of Gene Expression Profiles Reducing Based on the Complex Use of Fuzzy Inference System and Clustering Quality Criteria

“…In the case of the further reconstruction of genes regulatory network the third case is the optimal one since the number of the allocated genes allows us to reconstruct the genes network qualitative for purpose of the following investigation of the character of genes interconnection taking into account the status of the object. In the case of the step-by-step gene expression profiles clustering and biclustering for purpose of genes regulatory networks reconstruction [3] the first or the second cases are the optimal ones since the number of the allocated gene expression profiles allows us to implement the gene expression profiles clustering and biclustering for both the reconstruction of genes regulatory networks and simulation of the genes networks obtained models.…”

“…In any case we have as the result a high dimensional matrix, where number of rows is the number of the studied genes and number of columns is the number of the studied objects or conditions of the experiment performing. In paper [3] authors presented the results of the research concerning development of the information technology of gene expression profiles processing for purpose of gene regulatory networks reconstruction. The gene expression profiles reducing in terms of the statistical criteria and Shannon entropy is one of the stages of this technology implementation.…”

A Hybrid Model of 1-D Signal Adaptive Filter Based on the Complex Use of Huang Transform and Wavelet Analysis

“…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.…”