A REVIEW OF TOOLS, METHODOLOGIES, AND TECHNIQUES FOR PROCESSING, PRE-PROCESSING, AND CLUSTERING ANALYSIS OF GENETIC DATA

ГЕНЕТИКАЛЫҚ ДЕРЕКТЕРДІ ӨҢДЕУГЕ, АЛДЫН АЛА ӨҢДЕУ МЕН КЛАСТЕРЛІК ТАЛДАУҒА АРНАЛҒАН ҚҰРАЛДАРҒА, ӘДІСТЕМЕЛЕР МЕН ӘДІСТЕРГЕ ШОЛУ
ОБЗОР ИНСТРУМЕНТОВ, МЕТОДОЛОГИЙ И МЕТОДОВ ОБРАБОТКИ, ПРЕДВАРИТЕЛЬНОЙ ОБРАБОТКИ И КЛАСТЕРНОГО АНАЛИЗА ГЕНЕТИЧЕСКИХ ДАННЫХ
Kunikeyev A. Yerimbetova A. Satybaldiyeva R.
2024 Kazakh-British Technical University

Herald of the Kazakh British Technical UNiversity
2024 #21 Issue 4 45 - 57 pp.

Gene expression analysis has become a key component in understanding cellular behavior, disease mechanisms, and drug response. The advent of high-throughput sequencing, particularly single-cell RNA sequencing (scRNA-seq), has expanded our ability to study cellular heterogeneity to an unprecedented level. Clustering algorithms needed to group genes or cells with similar expression profiles have become invaluable for analyzing the massive data sets generated by these technologies. This article reviews various clustering methods applied to gene expression data, particularly single-cell RNA sequencing. The analysis covers traditional methods such as hierarchical clustering and k-means, as well as more advanced approaches such as model-based clustering, machine learning-based methods, and deep learning methods. The primary challenges encompass handling high-dimensional data, mitigating noise, and achieving scalability for large datasets. Moreover, new advancements such as multi-omics data integration, deep learning-based clustering, and federated learning offer potential enhancements in accuracy and biological relevance for clustering applications in gene expression research. The review concludes with a discussion of clustering algorithms in handling increasingly complex gene expression data for more accurate biological insights.

Bioinformatics , Clustering methods , Deep learning , Gene expressions , Machine Learning , single-cell RNA sequencing

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Satbayev University, Almaty, Kazakhstan
Institute of Information and Computational Technologies of the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan, Almaty, Kazakhstan

Satbayev University
Institute of Information and Computational Technologies of the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan

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