| Issue |
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
|
|
|---|---|---|
| Article Number | 01067 | |
| Number of page(s) | 10 | |
| DOI | https://doi.org/10.1051/e3sconf/202343001067 | |
| Published online | 06 October 2023 | |
Decoding the Human Genome: Machine Learning Techniques for DNA Sequencing Analysis
1 Department of CSE, GRIET, Bachupally, Hyderabad, 500090, India
2 Uttaranchal Institute of Management, Uttaranchal University, Dehradun, India
3 KG Reddy College of Engineering & Technology, Hyderabad, India
* Corresponding author: shanu.chintha@gmail.com
The decoding of the human genome has been a landmark achievement in the field of genomics, generating vast amounts of DNA sequencing data that necessitate sophisticated analysis techniques. In recent years, machine learning has emerged as a powerful tool in unravelling the complexities of genomic data and expediting research discoveries. This article explores the integration of machine learning techniques in DNA sequencing analysis, elucidating their applications in genome assembly, variant calling, personalized medicine, and drug discovery. Additionally, it addresses the ethical considerations surrounding the use of genomic data. By harnessing the potential of machine learning, researchers are unlocking new insights into human genetics and paving the way for transformative advancements in healthcare and scientific understanding.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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