Research on Sequence Clustering and Alignment in DNA Storage Based on the K-Means Model - Yang, Guanglin; Zhu, Yinting (Transactions on Materials, Biotechnology and Life Sciences, 2024)
The technology of DNA storage uses artificially synthesized deoxynucleotide chains to store information, ensuring precise and error-free reading. Compared with traditional electronic information storage, it has advantages in terms of capacity, density, and energy consumption. In this study, a K-Means clustering model is constructed with the aim of accurately clustering DNA sequences after DNA storage sequencing. To objectively evaluate the effectiveness of the model, clustering results are compared in detail with the correct DNA sequences. Experimental data show that when processing 100,000 DNA storage sequencing sequences, the accuracy of the model exceeds 90%, and the entire clustering process only takes 10 seconds. This result fully demonstrates the important role of the K-Means model in restoring original information sequences in DNA storage and provides a solid theoretical and practical foundation for future research.