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Compressive biological sequence analysis and archival in the era of high-throughput sequencing technologies.
Giancarlo, Raffaele; Rombo, Simona E; Utro, Filippo.
Afiliação
  • Giancarlo R; Dipartimento di Matematica ed Informatica, Università degli Studi di Palermo, Palermo, Italy. Tel.: (+39) 091 238 91067; Fax: (+39) 091 238 91024; raffaele@math.unipa.it; Simona E. Rombo, Dipartimento di Matematica ed Informatica, Università degli Studi di Palermo, Palermo, Italy. Tel.: (+39) 091 238 91028; Fax: (+39) 091 238 91024; E-mail: simona.rombo@math.unipa.it; Filippo Utro, Computational Genomics Group, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA. Tel.: (+1) 914 945 1549;
Brief Bioinform ; 15(3): 390-406, 2014 May.
Article em En | MEDLINE | ID: mdl-24347576
ABSTRACT
High-throughput sequencing technologies produce large collections of data, mainly DNA sequences with additional information, requiring the design of efficient and effective methodologies for both their compression and storage. In this context, we first provide a classification of the main techniques that have been proposed, according to three specific research directions that have emerged from the literature and, for each, we provide an overview of the current techniques. Finally, to make this review useful to researchers and technicians applying the existing software and tools, we include a synopsis of the main characteristics of the described approaches, including details on their implementation and availability. Performance of the various methods is also highlighted, although the state of the art does not lend itself to a consistent and coherent comparison among all the methods presented here.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia Computacional / Compressão de Dados / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Systematic_reviews Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia Computacional / Compressão de Dados / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Systematic_reviews Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2014 Tipo de documento: Article