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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha : |
17/04/2017 |
Actualizado : |
11/10/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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. |
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. |
Título : |
MEGARes: an antimicrobial resistance database for high throughput sequencing. |
Fecha de publicación : |
2017 |
Fuente / Imprenta : |
Nucleic Acids Research, 2017 v.45 p.574-580. |
DOI : |
10.1093/nar/gkw1009 |
Idioma : |
Inglés |
Notas : |
Article History: Published online 2016 Nov 24.
DOI: https://doi.org/10.1093/nar/gkw1009 |
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. |
Palabras claves : |
BASE DE DATOS; BIOINFORMÁTICA; DATASETS; DRUG RESISTANCE; GENES; METAGENÓMICA; METAGENOMICS; MICROBIAL; POLYMERASE CHAIN REACTION; PUBLIC HEALTH MEDICINE; RESISTENCIA ANTIMICROBIANA; SEQUENCE ANALYSIS. |
Asunto categoría : |
L01 Ganadería |
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 : |
LEADER 02505naa a2200433 a 4500 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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Registro original : |
INIA Treinta y Tres (TT) |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
Fecha actual : |
03/11/2014 |
Actualizado : |
22/02/2018 |
Tipo de producción científica : |
Software |
Autor : |
FASSIO, A.; IBAÑEZ, W.; RODRÍGUEZ, M.; CERETTA, S.; PÉREZ, O.; RABAZA, C.; VERGARA, A.; CESAN, A.; RESTAINO, E. |
Afiliación : |
ALBERTO SANTIAGO FASSIO ARAUJO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; WILFREDO ARIEL IBAÑEZ ALVEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARCELO JULIAN RODRIGUEZ ALONZO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SERGIO EDUARDO CERETTA SORIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OSVALDO MARTIN PEREZ GONZALEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS MARIANO RABAZA LOPEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GLENDA ALEJANDRA VERGARA GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ARIEL ESTEBAN CESAN LOPEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ERNESTO ANGEL RESTAINO GALUP, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Predicción de estados fenológicos de soja y otros cultivos de verano: ... soja, girasol, maíz, sorgo granífero, forrajero, dulce y silero. |
Fecha de publicación : |
2014 |
Fuente / Imprenta : |
Montevideo: INIA, 2014. |
Descripción física : |
Modelo de predicción fenológica en línea. |
Idioma : |
Español |
Thesagro : |
CULTIVOS DE VERANO; GIRASOL; GLYCINE MAX; HELIANTHUS ANNUUS; MAÍZ; MODELOS DE CRECIMIENTO; SOJA; SORGHUM; SORGO; ZEA MAYS. |
Asunto categoría : |
F01 Cultivo |
URL : |
http://www.inia.uy/gras/Alertas-y-herramientas/Utilidades
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Marc : |
LEADER 00929nam a2200325 a 4500 001 1051448 005 2018-02-22 008 2014 bl uuuu u0uu1 u #d 100 1 $aFASSIO, A. 245 $aPredicción de estados fenológicos de soja y otros cultivos de verano$b... soja, girasol, maíz, sorgo granífero, forrajero, dulce y silero.$h[electronic resource] 260 $aMontevideo: INIA$c2014 300 $cModelo de predicción fenológica en línea. 650 $aCULTIVOS DE VERANO 650 $aGIRASOL 650 $aGLYCINE MAX 650 $aHELIANTHUS ANNUUS 650 $aMAÍZ 650 $aMODELOS DE CRECIMIENTO 650 $aSOJA 650 $aSORGHUM 650 $aSORGO 650 $aZEA MAYS 700 1 $aIBAÑEZ, W. 700 1 $aRODRÍGUEZ, M. 700 1 $aCERETTA, S. 700 1 $aPÉREZ, O. 700 1 $aRABAZA, C. 700 1 $aVERGARA, A. 700 1 $aCESAN, A. 700 1 $aRESTAINO, E.
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INIA La Estanzuela (LE) |
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