Machine Learning Applications in Genomic Data Analysis

K. Sandhya Rani

doi:https://dx.doi.org/10.5281/zenodo.22896101

Review Article

Machine Learning Applications in Genomic Data Analysis

K. Sandhya Rani

Department of Computer Science, Govt. Degree College, Dharpally, Telangana State, India

Article ID: AJSMR-2026-53637 | DOI: https://dx.doi.org/10.5281/zenodo.22896101

Issue: Vol. 12 No. 3 (2026) | Pages: 47–49

Abstract

The rapid advancement of next-generation sequencing technologies has led to the generation of massive genomic datasets, creating more opportunities and challenges in biological research. Analyzing such complex and high-dimensional data requires advanced computational methods. Machine learning (ML), a branch of artificial intelligence, has emerged as a powerful tool for extracting meaningful insights from genomic data. ML algorithms enable the identification of patterns, prediction of gene functions, classification of biological sequences, and detection of genetic variations associated with diseases. This paper reviews the role of machine learning techniques in genomic data analysis and highlights their applications in gene prediction, gene expression analysis, disease diagnosis, and personalized medicine. The study also discusses commonly used machine learning algorithms such as support vector machines, decision trees, neural networks, and deep learning models. Furthermore, challenges and future prospects of applying machine learning in genomics are discussed. The integration of machine learning with bioinformatics tools offers promising opportunities for improving genomic research, accelerating biomedical discoveries, and supporting the development of precision medicine.

Machine LearningGenomicsBioinformaticsArtificial IntelligenceGene PredictionPrecision Medicine

About this Article

Article Type	Review Article
Article ID	AJSMR-2026-53637
Issue	Vol. 12 No. 3 (2026)
Section	Articles
DOI	https://dx.doi.org/10.5281/zenodo.22896101
Pages	47–49
Published	22 September 2026
Keywords	Machine Learning, Genomics, Bioinformatics, Artificial Intelligence, Gene Prediction, Precision Medicine
Access	Open Access
License	CC BY 4.0

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How to Cite

AJSMR provides three commonly used citation formats below. APA is displayed first as the primary citation format, followed by Vancouver and Harvard styles.

APA 7th Edition

Rani, K. S. (2026). Machine Learning Applications in Genomic Data Analysis. The American Journal of Science and Medical Research, 12(3), 47–49. https://dx.doi.org/10.5281/zenodo.22896101

Vancouver

K. SR. Machine Learning Applications in Genomic Data Analysis. Am J Sci Med Res. 2026;12(3):47–49. doi:10.5281/zenodo.22896101

Harvard

Rani, K. S. 2026, 'Machine Learning Applications in Genomic Data Analysis', Am J Sci Med Res, 12(3), pp. 47–49. Available at: https://dx.doi.org/10.5281/zenodo.22896101

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