On the synthesis of DNA error correcting codes
DNA error correcting codes over the edit metric consist of embeddable markers for sequencing projects that are tolerant of sequencing errors. When a genetic library has multiple sources for its sequences, use of embedded markers permit tracking of sequence origin. This study compares different metho...
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| Published in | BioSystems Vol. 110; no. 1; pp. 1 - 8 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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Elsevier Ireland Ltd
01.10.2012
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| Online Access | Get full text |
| ISSN | 0303-2647 1872-8324 1872-8324 |
| DOI | 10.1016/j.biosystems.2012.06.005 |
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| Abstract | DNA error correcting codes over the edit metric consist of embeddable markers for sequencing projects that are tolerant of sequencing errors. When a genetic library has multiple sources for its sequences, use of embedded markers permit tracking of sequence origin. This study compares different methods for synthesizing DNA error correcting codes. A new code-finding technique called the salmon algorithm is introduced and used to improve the size of best known codes in five difficult cases of the problem, including the most studied case: length six, distance three codes. An updated table of the best known code sizes with 36 improved values, resulting from three different algorithms, is presented. Mathematical background results for the problem from multiple sources are summarized. A discussion of practical details that arise in application, including biological design and decoding, is also given in this study. |
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| AbstractList | DNA error correcting codes over the edit metric consist of embeddable markers for sequencing projects that are tolerant of sequencing errors. When a genetic library has multiple sources for its sequences, use of embedded markers permit tracking of sequence origin. This study compares different methods for synthesizing DNA error correcting codes. A new code-finding technique called the salmon algorithm is introduced and used to improve the size of best known codes in five difficult cases of the problem, including the most studied case: length six, distance three codes. An updated table of the best known code sizes with 36 improved values, resulting from three different algorithms, is presented. Mathematical background results for the problem from multiple sources are summarized. A discussion of practical details that arise in application, including biological design and decoding, is also given in this study. DNA error correcting codes over the edit metric consist of embeddable markers for sequencing projects that are tolerant of sequencing errors. When a genetic library has multiple sources for its sequences, use of embedded markers permit tracking of sequence origin. This study compares different methods for synthesizing DNA error correcting codes. A new code-finding technique called the salmon algorithm is introduced and used to improve the size of best known codes in five difficult cases of the problem, including the most studied case: length six, distance three codes. An updated table of the best known code sizes with 36 improved values, resulting from three different algorithms, is presented. Mathematical background results for the problem from multiple sources are summarized. A discussion of practical details that arise in application, including biological design and decoding, is also given in this study.DNA error correcting codes over the edit metric consist of embeddable markers for sequencing projects that are tolerant of sequencing errors. When a genetic library has multiple sources for its sequences, use of embedded markers permit tracking of sequence origin. This study compares different methods for synthesizing DNA error correcting codes. A new code-finding technique called the salmon algorithm is introduced and used to improve the size of best known codes in five difficult cases of the problem, including the most studied case: length six, distance three codes. An updated table of the best known code sizes with 36 improved values, resulting from three different algorithms, is presented. Mathematical background results for the problem from multiple sources are summarized. A discussion of practical details that arise in application, including biological design and decoding, is also given in this study. |
| Author | Ashlock, Daniel Orth, John Brown, Joseph Alexander Houghten, Sheridan K. |
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| Keywords | Representation Error correcting code Evolutionarycomputation Nucleic acids Next-gen sequencing Bioinformatics |
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| References_xml | – start-page: 103 year: 2010 end-page: 110 ident: bib0050 article-title: Side effect machines for quaternary edit metric decoding publication-title: Proceedings of the 2010 IEEE Symposium on Bioinformatics and Computational Biology – volume: 64 start-page: 10 year: 1993 end-page: 30 ident: bib0060 article-title: Greedy codes publication-title: J. Comb. Theory(A) – start-page: 259 year: 2006 end-page: 263 ident: bib0080 article-title: Construction of optimal edit metric codes publication-title: Proceedings of the 2006 IEEE Workshop on Information Theory – start-page: 222 year: 2010 end-page: 229 ident: bib0035 article-title: Ring optimization of dna edit metric codes publication-title: Proceedings of ACM-BCB 2010 – reference: Campbell, J.K., 2005. Enumeration and symmetry of edit metric spaces. 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| SubjectTerms | Algorithms Bioinformatics Computational Biology DNA DNA Repair DNA Replication Error correcting code Evolutionarycomputation Gene Library monitoring Next-gen sequencing Nucleic acids Representation salmon |
| Title | On the synthesis of DNA error correcting codes |
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