Sergii Babichev

• Doctor of Science
• Professor at Kherson State University

The growing volume and complexity of gene expression data necessitate biologically meaningful and statistically robust methods for feature selection to enhance the effectiveness of disease diagnosis systems. The present study addresses this challenge by proposing a pipeline that integrates RNA-seq data preprocessing, differential gene expression an...

The manuscript details the outcomes of a comprehensive study on the application of cluster-bicluster analysis, gene ontology analysis, and convolutional neural network (CNN) for diagnosing cancer and Alzheimer’s disease using gene expression data derived from both DNA microarray experiments and mRNA sequencing. It outlines a conceptual framework an...

This manuscript explores the application of deep learning (DL) techniques for classifying gene expression data. A key aspect of our research is the comparative analysis of various DL neural network architectures, including Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) Recurrent Neural Networks (RNN)...

The importance of gene expression data processing in solving the classification task is determined by its ability to discern intricate patterns and relationships within genetic information, enabling the precise categorization and understanding of various gene expression profiles and their consequential impacts on biological processes and traits. In...

One of the current focuses of modern bioinformatics is the development of hybrid models to process gene expression data, in order to create diagnostic systems for various diseases. In this study, we propose a solution to this problem that combines an inductive spectral clustering algorithm, random forest classifier, convolutional neural network, an...

The development of hybrid models focused on gene expression data processing for the allocation of differentially expressed and mutually correlated genes is one of the current directions in modern bioinformatics. The solution to this problem can allow us to improve the effectiveness of existing systems for complex diseases diagnosis based on gene ex...

The results of research regarding the development of a gene expression data classification system based on a convolutional neural network are presented. Gene expression data of patients who were studied for lung cancer were used as experimental data. 156 patients were studied, of which 65 were identified as healthy and 91 patients were diagnosed wi...

The paper presents the results of the research regarding the application of a fuzzy logic inference system to form the co-expressed gene expression profiles based on the joint use of Shannon entropy and statistical criteria . The allocation of co-expressed genes can allow us to increase the disease diagnosis accuracy on the one hand and, reconstruc...

The problems of gene regulatory network (GRN) reconstruction and the creation of disease diagnostic effective systems based on genes expression data are some of the current directions of modern bioinformatics. In this manuscript, we present the results of the research focused on the evaluation of the effectiveness of the most used metrics to estima...

In this paper, we present the model of assessment of higher education school academic staff members rating based on the complex use of Harrington’s desirability function and a fuzzy inference system. Four main directions of activity were evaluated within the framework of the proposed model: pedagogical activity; science and research; organization a...

An application of both the DNA microchips tests or RNA molecules sequencing experiments allows us to form the high-dimensional matrix of genes expressions, values of which are proportional to the number of the appropriate type of genes that matched the respectively investigated sample. In the general instance, the number of genes can achieve tens o...

The paper presents the results of the research concerning development of a fuzzy inference system to determine the current state of marine engine based on criteria established by the manufacturer. The practical implementation of the proposed model has been carried out for marine engine Wärtsilä 6L46C, which is one of the most used types of current...

In this paper, we have presented a results of the research concerning selection of informative genes based on the complex use of both statistical criteria and Shannon entropy. The main objective of the research is development a technique of selection of the groups of gene expression profiles which allow dividing correctly the investigated samples i...

In this paper, we have presented the research results concerning analysis of gene regulatory network structure based on Cytoscape software tools using graph theory. The gene regulatory network reconstructed using gene expression profiles of patients which were investigated on Alzheimer disease was used as an experimental one during the simulation p...

This book includes 46 scientific papers presented at the conference and reflecting the latest research in the fields of data mining, machine learning and decision-making. The international scientific conference “Intellectual Systems of Decision-Making and Problems of Computational Intelligence” was held in the Kherson region, Ukraine, from May 25 t...

The results of the research concerning development of the technique of metals strength properties diagnostics using combination of the methods of non-destructive control based on the complex use of fuzzy inference system and hybrid neural network are presented in the paper. The acoustic non-destructive control method, the electro-magnetic method an...

In this paper, we present the results of the research concerning comparison analysis of both the internal and external clustering quality criteria for clustering various types of datasets using density-based DBSCAN clustering algorithm implemented based on Inductive Methods of Objective Clustering (IMOC). Implementation of the IMOC technique assume...

In this paper, we present the results of the research concerning extraction of informative gene expression profiles from high-dimensional array of gene expressions considering the state of patients’ health using clustering method, ML-based binary classifiers and fuzzy inference system. Applying of the proposed stepwise procedure can allow us to ext...

In this paper, we present the results of the research concerning extraction of informative gene expression profiles from high-dimensional array of gene expressions considering the state of patients' health using clustering method, ensemble of binary classifiers and fuzzy inference system. Applying of the proposed stepwise procedure can allow us to...

The paper presents the results of the research concerning comparison analysis of the efectiveness of OPTICS and DBSCAN density-based and agglonarative hierarchical clustering algorithms within the framework of the objective clustering inductive technology. Implementation of this technology allows us to determine the optimal parameters of appropriat...

Technological stages or separate procedures of the publishing and printing process involve relevant databases and a set of factors (criteria, parameters, requirements) to ensure their quality implementation. However, they are different in nature, purpose, setting type, peculiarities of impact and application methods, that complicates the generaliza...

The paper presents the results of the research concerning development of acoustic emission signals soft filtering model based on the complex use of Huang transform and wavelet analysis. The acoustic emission signals which were generated during crack progression from initiation to final failure with several distinct phases have been used as the expe...

This book constitutes the proceedings of the third International Conference on Data Stream and Mining and Processing, DSMP 2020, held in Lviv, Ukraine*, in August 2020. The 36 full papers presented in this volume were carefully reviewed and selected from 134 submissions. The papers are organized in topical sections of hybrid systems of computationa...

Context. The problem of the data clustering within the framework of the objective clustering inductive technology is considered. Practical implementation of the obtained hybrid model based on the complex use of R and KNIME tools is performed. The object of the study is the hybrid model of the data clustering based on the complex use of both DBSCAN...

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...

This paper presents the results of research concerning the evaluation of stability of information technology of gene expression profiles processing with the use of gene expression profiles, which contain different levels of noise components. The information technology is presented as a structural block-chart, which contains all stages of the studie...

The paper presents the results of the research concerning an evaluation of information 1 technology of gene expression profiles processing stability with the use of gene expression profiles 2 with different levels of noise component. The information technology is presented as a structural 3 block-chart, which contains all stages of the studied data...

The paper presents the hybrid model of the objective clustering inductive technology based on complex using of the self-organizing SOTA and the density DBSCAN clustering algorithms. The inductive methods of complex systems analysis were used as the basis to implement the objective clustering inductive technology of gene expression profiles. To esti...

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 patie...

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 perfo...

The paper presents the research concerning comparison analysis of biclustering algorithms effectiveness with the use of artificial data and gene expression profiles. Internal biclustering quality criterion is proposed as the result of the simulation. The change of this criterion has high correlation with Jaccard index, which was calculated for perf...

Aim. Development of an inductive technology of objective clustering of gene expression profiles based on a self-organizing SOTA clustering algorithm. Methods. Inductive methods of complex system analysis were used to implement the inductive technology of objective clustering of gene expression profiles. The optimal parameters of clustering algorith...

Technology of high dimensional data features objective clustering based on the methods of complex systems inductive modeling is presented in the paper. Architecture of the objective clustering inductive technology as a block diagram of step-by-step implementation of the objects clustering procedure was developed. Method of criterial evaluation of c...

The inductive model of the objective clustering of objects based on the k-means algorithm clustering is presented in the paper. The algorithm for division of initial data into two equal power subsets is proposed and practically implemented. The difference between the mass centres of the appropriate clusters in different clustering is proposed to us...

Model of data clustering system based on the complex use of agglomerative hierarchical algorithm and inductive modeling methods of complex systems is presented in the paper. The quality of clustering is evaluated by two equal power subsets with the use of complex balance criterion, which takes into account both the displacement the mass centers of...

Researches on an optimization of the filtration process of DNA nucleotides gene expression profiles are presented in the article. The data of lung cancer patients E-GEOD-68571 of Array Express database were used as experimental data. Filtration was carried out under the terms of the expression detecting of corresponding gene, herewith the variance...

Aim. The article is dedicated to 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....

Babichev S., Osypenko V., Taif M., Lytvynenko V. Індуктивне моделювання складних систем, випуск 7, 2015 5 UDC 004.048 Досліджена можливість застосування бікластерного аналізу в системах кластеризації об'єктів складної біологічної природи. Бікластерізація проводилася за алгоритмом ВССС пакету "biclust" програмного середовища R, кластеризація об'єкті...

The methodic of choice of optimal normalization method for object cluster structure of creation, with high dimension of feature space, is shown. The Shannon entropy criterion and entropy relative change were used as main criterions of estimating the data preprocessing quality during the data transformation. Decreasing of feature space dimension of...