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| Registros recuperados : 33 | |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
17/04/2017 |
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Actualizado : |
11/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - A |
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Autor : |
LAKIN, S.M.; DEAN, C.; NOYES, N.R.; DETTENWANGER, A.; ROSS, A. S.; DOSTER, E.; ROVIRA, P.J.; ABDO, Z.; JONES, K.L.; RUIZ, J.; BELK, K.E.; MORLEY, P.S.; BOUCHER, C. |
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Afiliación : |
STEVEN M. LAKIN; CHRIS DEAN; NOELLE R. NOYES; ADAM DETTENWANGER; ANNE SPENCER ROSS; ENRIQUE DOSTER; PABLO JUAN ROVIRA SANZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. Department of Animal Sciences, Colorado State University, USA.; ZAID ABDO; KENNETH L. JONES; JAIME RUIZ; KEITH E. BELK; PAUL S. MORLEY; CHRISTINA BOUCHER. |
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Título : |
MEGARes: an antimicrobial resistance database for high throughput sequencing. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Nucleic Acids Research, 2017 v.45 p.574-580. |
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DOI : |
10.1093/nar/gkw1009 |
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Idioma : |
Inglés |
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Notas : |
Article History: Published online 2016 Nov 24.
DOI: https://doi.org/10.1093/nar/gkw1009 |
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Contenido : |
Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database. |
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Palabras claves : |
BASE DE DATOS; BIOINFORMÁTICA; DATASETS; DRUG RESISTANCE; GENES; METAGENÓMICA; METAGENOMICS; MICROBIAL; POLYMERASE CHAIN REACTION; PUBLIC HEALTH MEDICINE; RESISTENCIA ANTIMICROBIANA; SEQUENCE ANALYSIS. |
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Asunto categoría : |
L01 Ganadería |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/6677/1/Rovira-arb-2017-1.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210519/
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Marc : |
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001 1057051
005 2019-10-11
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1093/nar/gkw1009$2DOI
100 1 $aLAKIN, S.M.
245 $aMEGARes$ban antimicrobial resistance database for high throughput sequencing.$h[electronic resource]
260 $c2017
500 $aArticle History: Published online 2016 Nov 24. DOI: https://doi.org/10.1093/nar/gkw1009
520 $aAntimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database.
653 $aBASE DE DATOS
653 $aBIOINFORMÁTICA
653 $aDATASETS
653 $aDRUG RESISTANCE
653 $aGENES
653 $aMETAGENÓMICA
653 $aMETAGENOMICS
653 $aMICROBIAL
653 $aPOLYMERASE CHAIN REACTION
653 $aPUBLIC HEALTH MEDICINE
653 $aRESISTENCIA ANTIMICROBIANA
653 $aSEQUENCE ANALYSIS
700 1 $aDEAN, C.
700 1 $aNOYES, N.R.
700 1 $aDETTENWANGER, A.
700 1 $aROSS, A. S.
700 1 $aDOSTER, E.
700 1 $aROVIRA, P.J.
700 1 $aABDO, Z.
700 1 $aJONES, K.L.
700 1 $aRUIZ, J.
700 1 $aBELK, K.E.
700 1 $aMORLEY, P.S.
700 1 $aBOUCHER, C.
773 $tNucleic Acids Research, 2017$gv.45 p.574-580.
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