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Viral Genome Compression
Viruses compress their genome to reduce space. One of the main techniques is overlapping genes. We model this process by the shortest common superstring problem, that is, we look for the shortest genome which still contains all genes. We give an algorithm for computing optimal solutions which is slo...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2006
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7121740/ http://dx.doi.org/10.1007/11925903_9 |
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author | Ilie, Lucian Tinta, Liviu Popescu, Cristian Hill, Kathleen A. |
author_facet | Ilie, Lucian Tinta, Liviu Popescu, Cristian Hill, Kathleen A. |
author_sort | Ilie, Lucian |
collection | PubMed |
description | Viruses compress their genome to reduce space. One of the main techniques is overlapping genes. We model this process by the shortest common superstring problem, that is, we look for the shortest genome which still contains all genes. We give an algorithm for computing optimal solutions which is slow in the number of strings but fast (linear) in their total length. This algorithm is used for a number of viruses with relatively few genes. When the number of genes is larger, we compute approximate solutions using the greedy algorithm which gives an upper bound for the optimal solution. We give also a lower bound for the shortest common superstring problem. The results obtained are then compared with what happens in nature. Remarkably, the compression obtained by viruses is quite high and also very close to the one achieved by modern computers. |
format | Online Article Text |
id | pubmed-7121740 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71217402020-04-06 Viral Genome Compression Ilie, Lucian Tinta, Liviu Popescu, Cristian Hill, Kathleen A. DNA Computing Article Viruses compress their genome to reduce space. One of the main techniques is overlapping genes. We model this process by the shortest common superstring problem, that is, we look for the shortest genome which still contains all genes. We give an algorithm for computing optimal solutions which is slow in the number of strings but fast (linear) in their total length. This algorithm is used for a number of viruses with relatively few genes. When the number of genes is larger, we compute approximate solutions using the greedy algorithm which gives an upper bound for the optimal solution. We give also a lower bound for the shortest common superstring problem. The results obtained are then compared with what happens in nature. Remarkably, the compression obtained by viruses is quite high and also very close to the one achieved by modern computers. 2006 /pmc/articles/PMC7121740/ http://dx.doi.org/10.1007/11925903_9 Text en © Springer-Verlag Berlin Heidelberg 2006 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Ilie, Lucian Tinta, Liviu Popescu, Cristian Hill, Kathleen A. Viral Genome Compression |
title | Viral Genome Compression |
title_full | Viral Genome Compression |
title_fullStr | Viral Genome Compression |
title_full_unstemmed | Viral Genome Compression |
title_short | Viral Genome Compression |
title_sort | viral genome compression |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7121740/ http://dx.doi.org/10.1007/11925903_9 |
work_keys_str_mv | AT ilielucian viralgenomecompression AT tintaliviu viralgenomecompression AT popescucristian viralgenomecompression AT hillkathleena viralgenomecompression |