Titre : Scalable and Accurate Algorithms for Computational Genomics and DNA-based Digital Storage
Date : 26 avril 2023
Résumé : Cost reduction and throughput improvement in sequencing technology have resulted in new advances in some applications such as precision medicine, DNA-based storage. However, the sequenced result contains errors. To measure the similarity between the sequenced result and reference, edit distance is preferred in practice over Hamming distance due to the indels. The primary edit distance calculation is quadratic complex. Therefore, sequence similarity analysis is computationally intensive. In this thesis, we introduce two accurate and scalable sequence similarity analysis algorithms, i) Accel-Align, a fast sequence mapper and aligner based on the seed–embed–extend method, and ii) Motif-Search, an efficient structure-aware algorithm to recover the information in DNA-based storage. Then, we use Accel-Align as an efficient tool to study the random access design in DNA-based storage.
Lieu : Eurecom