Unraveling Genetic Complexity: Fine-tuning Machine Learning Models for DNA Sequence Analysis with K-mer Size

In the realm of genetic analysis, the utilization of machine learning models holds great potential for unraveling the intricate complexities of DNA sequence data. This study aims to address the pressing need for advanced DNA sequence analysis methods by leveraging K-mer representations and fine-tuning machine learning algorithms to achieve optimal performance. By elucidating the reasons behind the study and highlighting the significance of these approaches, this research contributes to the broader understanding of DNA sequence intricacies.