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Highly scalable algorithms for robust string barcoding

  • B. DasGupta(corresponding author)
    ,
  • K. M. Konwar
    ,
  • I. I. Mǎndoiu
    ,
*Corresponding author for this work
  • University of Illinois at Chicago
    ,
  • University of Connecticut
Scholary Output:
Contribution to journal
Conference article
Peer-review

Open access

Related Event

Title

5th International Conference on Computational Science - ICCS 2005

Event type

Conference

Date

05/22/2005 - 05/25/2005

Location

Atlanta, GAUnited States

Abstract

String barcoding is a recently introduced technique for genomic-based identification of microorganisms. In this paper we describe the engineering of highly scalable algorithms for robust string barcoding. Our methods enable distinguisher selection based on whole genomic sequences of hundreds of microorganisms of up to bacterial size on a well-equipped workstation, and can be easily parallelized to further extend the applicability range to thousands of bacterial size genomes. Experimental results on both randomly generated and NCBI genomic data show that whole-genome based selection results in a number of distinguishers nearly matching the information theoretic lower bounds for the problem.

Publication Information

Output type

Scholary Output:
Contribution to journal
Conference article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 1020-1028 (9 pages)

Journal (Volume, Issue Number)

Lecture Notes in Computer Science (Volume 3515, Issue II)

Publication milestones

  • Published - 2005

Publication status

Published - 2005

ISSN

0302-9743

Publication IDs

  • Scopus: 25144505788

Publication metrics

Metrics

Scopus
citations
Fractional count
1
Fractional count
0.25
Fractional count
3
Fractional count
0.75
Fractional count
1
Fractional count
1

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Citation count
2
Captures
2

Funding Details

FunderFunding number
-
0346973