A scalable parallel reconfigurable hardware architecture for DNA matching |
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| Affiliation: | 1. Department of Electronics Engineering and Telecommunications, State University of Rio de Janeiro, Brazil;2. Department of Systems Engineering and Computation, State University of Rio de Janeiro, Brazil;1. Department of Electronics and Instrumentation Technology, University of Kashmir, Srinagar, Jammu and Kashmir, 190006, India;2. Department of Electronics, Islamia College of Science and Commerce, Srinagar, Jammu and Kashmir, India;1. Department of IT, Vasavi College of Engineering, Hyderabad, India;2. Department of Electrical and Electronics Engineering, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, 517102, India;3. Department of Computer Science & Engineering, Anurag University, Medchal, Hyderabad, Telangana, 500088, India;4. Department of Computer Science and Engineering, Narsimha Reddy Engineering College, Kompally, Hyderabad, 500100, Telangana State, India;5. Department of Information Technology, Kakatiya Institute of Technology and Science, Warangal, Telangana, 506015, India;6. Department of Electronics and Communication Engineering, Prathyusha Engineering College, Aranvoyalkuppam, Thiruvallur, 602025, India;1. Department of Electronics, Mangalore University, Karnataka, India;2. RV College of Engineering, Bangalore, Karnataka India;1. Natural Resources Canada, CanmetENERGY, 1 Haanel Dr., Ottawa, ON, Canada;2. Natural Resources Canada, CanmetENERGY, 1615 Lionel-Boulet Blvd., Varennes, QC, Canada |
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| Abstract: | DNA sequence matching is used in the identification of a relationship between a fragment of DNA and its owner by mean of a database of DNA registers. A DNA fragment could be a hair sample left at a crime scene by a suspect or provided by a person for a paternity exam. The process of aligning and matching DNA sequences is a computationally demanding process. In this paper, we propose a novel parallel hardware architecture for DNA matching based on the steps of the BLAST algorithm. The design is scalable so that its structure can be adjusted depending on the size of the subject and query DNA sequences. Moreover, the number of units used to perform in parallel can also be scaled depending some characteristics of the algorithm. The design was synthesized and programmed into FPGA. The trade-off between cost and performance were analyzed to evaluate different design configuration. |
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