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- W2466826145 abstract "Computational genomics is an emerging field that is enabling us to reveal the origins of life and the genetic basis of diseases such as cancer. Next Generation Sequencing (NGS) technologies have unleashed a wealth of genomic information by producing immense amounts of raw data. Before any functional analysis can be applied to this data, read alignment is applied to find the genomic coordinates of the produced sequences. Alignment algorithms have evolved rapidly with the advancement in sequencing technology, striving to achieve biological accuracy at the expense of increasing space and time complexities. Hardware approaches have been proposed to accelerate the computational bottlenecks created by the alignment process. Although several hardware approaches have achieved remarkable speedups, most have overlooked important biological features, which have hampered their widespread adoption by the genomics community. In this paper, we provide a brief biological introduction to genomics and NGS. We discuss the most popular next generation read alignment tools and algorithms. Furthermore, we provide a comprehensive survey of the hardware implementations used to accelerate these algorithms." @default.
- W2466826145 created "2016-07-22" @default.
- W2466826145 creator A5021685706 @default.
- W2466826145 creator A5039285262 @default.
- W2466826145 creator A5045462352 @default.
- W2466826145 date "2017-11-01" @default.
- W2466826145 modified "2023-10-16" @default.
- W2466826145 title "A Survey of Software and Hardware Approaches to Performing Read Alignment in Next Generation Sequencing" @default.
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- W2466826145 doi "https://doi.org/10.1109/tcbb.2016.2586070" @default.
- W2466826145 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/27362989" @default.
- W2466826145 hasPublicationYear "2017" @default.
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