| Autor: |
Jinane Bazzi, Jana Sweidan, Mohammed E. Fouda, Rouwaida Kanj, Ahmed M. Eltawil |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Frontiers in Electronics, Vol 4 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2673-5857 |
| DOI: |
10.3389/felec.2023.1343612 |
| Popis: |
DNA pattern matching is essential for many widely used bioinformatics applications. Disease diagnosis is one of these applications since analyzing changes in DNA sequences can increase our understanding of possible genetic diseases. The remarkable growth in the size of DNA datasets has resulted in challenges in discovering DNA patterns efficiently in terms of run time and power consumption. In this paper, we propose an efficient pipelined hardware accelerator that determines the chance of the occurrence of repeat-expansion diseases using DNA pattern matching. The proposed design parallelizes the DNA pattern matching task using associative memory realized with analog content-addressable memory and implements an algorithm that returns the maximum number of consecutive occurrences of a specific pattern within a DNA sequence. We fully implement all the required hardware circuits with PTM 45-nm technology, and we evaluate the proposed architecture on a practical human DNA dataset. The results show that our design is energy-efficient and accelerates the DNA pattern matching task by more than 100× compared to the approaches described in the literature. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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