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New Generations: Sequencing Machines and Their Computational Challenges

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Abstract

New generation sequencing systems are changing how molecular biology is practiced. The widely promoted $1000 genome will be a reality with attendant changes for healthcare, including personalized medicine. More broadly the genomes of many new organisms with large samplings from populations will be commonplace. What is less appreciated is the explosive demands on computation, both for CPU cycles and storage as well as the need for new computational methods. In this article we will survey some of these developments and demands.

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Author information

Authors and Affiliations

  1. Laboratory for Molecular and Computational Genomics, Department of Chemistry and Laboratory of Genetics, University of Wisconsin-Madiso, Wisconsin, WI, 53706, U.S.A.

    David C. Schwartz

  2. Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089-2910, U.S.A.

    Michael S. Waterman

  3. Department of Automation, Tsinghua University, Beijing, 100084, China

    Michael S. Waterman

Authors
  1. David C. Schwartz
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  2. Michael S. Waterman
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Correspondence to David C. Schwartz.

Additional information

This work is supported by NIH under Grant No. R01 HG000225 (DCS) and NSF of USA under Grant No. DBI-0501818 (DCS).

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Schwartz, D.C., Waterman, M.S. New Generations: Sequencing Machines and Their Computational Challenges. J. Comput. Sci. Technol. 25, 3–9 (2010). https://doi.org/10.1007/s11390-010-9300-x

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  • DOI: https://doi.org/10.1007/s11390-010-9300-x

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