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Query Languages and Evaluation Techniques for Biological Sequence Data

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Encyclopedia of Database Systems

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Synonyms

Querying DNA sequences; Querying protein sequences

Definition

A common type of data that is used in life science applications is biological sequence data. Data such as DNA sequence and protein sequence data are growing at a very fast rate. For example, the data at GenBank[GB07] has been growing exponentially, doubling roughly every 18 months. These sequence datasets are often queried in complex ways and the methods required to query these sequences go far beyond the simple string matching methods that have been used in more traditional string applications. In order to enable users to easily pose sophisticated queries on these biological sequences, different languages have been designed to support a rich library of functions. In addition, some database systems have been extended to support a rich set of operators on the sequence data type. Compared to the stand-alone approach, the database method brings the power of algebraic query optimization and the use of indexes making it...

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Author information

Authors and Affiliations

  1. IBM Almaden Research Center, San Jose, CA, USA

    Sandeep Tata

  2. University of Wisconsin-Madison, Madison, WI, USA

    Jignesh M. Patel

Authors
  1. Sandeep Tata
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  2. Jignesh M. Patel
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Corresponding author

Correspondence to Sandeep Tata .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, Georgia, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, Ontario, Canada

    M. Tamer Özsu

Section Editor information

  1. Robert H. Smith School of Business, University of Maryland, Van Munching Hall (Mowatt Lane), 20742, College Park, MD, USA

    Louiqa Raschid

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Tata, S., Patel, J.M. (2016). Query Languages and Evaluation Techniques for Biological Sequence Data. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_630-2

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_630-2

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4899-7993-3

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