Literature DB >> 16895600

The approximability of the String Barcoding problem.

Giuseppe Lancia1, Romeo Rizzi.   

Abstract

The String Barcoding (SBC) problem, introduced by Rash and Gusfield (RECOMB, 2002), consists in finding a minimum set of substrings that can be used to distinguish between all members of a set of given strings. In a computational biology context, the given strings represent a set of known viruses, while the substrings can be used as probes for an hybridization experiment via microarray. Eventually, one aims at the classification of new strings (unknown viruses) through the result of the hybridization experiment. In this paper we show that SBC is as hard to approximate as Set Cover. Furthermore, we show that the constrained version of SBC (with probes of bounded length) is also hard to approximate. These negative results are tight.

Entities:  

Year:  2006        PMID: 16895600      PMCID: PMC1590015          DOI: 10.1186/1748-7188-1-12

Source DB:  PubMed          Journal:  Algorithms Mol Biol        ISSN: 1748-7188            Impact factor:   1.405


  3 in total

1.  Probe selection algorithms with applications in the analysis of microbial communities.

Authors:  J Borneman; M Chrobak; G Della Vedova; A Figueroa; T Jiang
Journal:  Bioinformatics       Date:  2001       Impact factor: 6.937

2.  DNA-BAR: distinguisher selection for DNA barcoding.

Authors:  B DasGupta; K M Konwar; I I Mandoiu; A A Shvartsman
Journal:  Bioinformatics       Date:  2005-06-16       Impact factor: 6.937

3.  Highly scalable algorithms for robust string barcoding.

Authors:  Bhaskar Dasgupta; Kishori M Konwar; Ion I Mandoiu; Alex A Shvartsman
Journal:  Int J Bioinform Res Appl       Date:  2005
  3 in total

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