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- W2999159028 abstract "Fast sequencing and analysis of (microorganism, plant or human) genomes will open up new vistas in fields like personalised medication, food yield and epigenetic research. Current state-of-the-art DNA pattern matching techniques use heuristic algorithms on computing clusters of CPUs, GPUs and FPGAs. With genomic data set to eclipse social and astronomical big data streams within a decade, the alternate computing paradigm of quantum computation is explored to accelerate genome-sequence reconstruction. The inherent parallelism of quantum superposition of states is harnessed to design a quantum kernel for accelerating the search process. The project explores the merger of these two domains and identifies ways to fit these together to design a genome-sequence analysis pipeline with quantum algorithmic speedup. The design of a genome-sequence analysis pipeline with a quantum kernel is tested with a proof-of-concept demonstration using a quantum simulator." @default.
- W2999159028 created "2020-01-23" @default.
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- W2999159028 date "2018-01-01" @default.
- W2999159028 modified "2023-09-27" @default.
- W2999159028 title "Quantum Algorithms: for pattern-matching in genomic sequences" @default.
- W2999159028 hasPublicationYear "2018" @default.
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