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Biblioteca (s) : |
INIA Tacuarembó. |
Fecha : |
21/02/2014 |
Actualizado : |
16/01/2019 |
Tipo de producción científica : |
Artículos en Revistas Agropecuarias |
Autor : |
TORRES, D. |
Afiliación : |
DIEGO GABRIEL TORRES DINI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Avances y potencialidades de marcadores moleculares en la genética forestal |
Fecha de publicación : |
2010 |
Fuente / Imprenta : |
Forestal: revista de la Sociedad de Productores Forestales, 2010, época 2, v. 14, no. 41, p. 13-16 |
Idioma : |
Español |
Contenido : |
Este trabajo describe los avances logrados hasta el momento en la identificación clonal de materiales de elite y finaliza con una breve revisión sobre en el potencial que tiene de la disciplina para los programas de mejoramiento genético. |
Palabras claves : |
IDENTIFICACIÓN CLONAL; MEJORAMIENTO GENÉTICO. |
Thesagro : |
MARCADORES GENETICOS. |
Asunto categoría : |
A50 Investigación agraria |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12285/1/41-2010.pdf
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Marc : |
LEADER 00752naa a2200157 a 4500 001 1028731 005 2019-01-16 008 2010 bl uuuu u00u1 u #d 100 1 $aTORRES, D. 245 $aAvances y potencialidades de marcadores moleculares en la genética forestal 260 $c2010 520 $aEste trabajo describe los avances logrados hasta el momento en la identificación clonal de materiales de elite y finaliza con una breve revisión sobre en el potencial que tiene de la disciplina para los programas de mejoramiento genético. 650 $aMARCADORES GENETICOS 653 $aIDENTIFICACIÓN CLONAL 653 $aMEJORAMIENTO GENÉTICO 773 $tForestal: revista de la Sociedad de Productores Forestales, 2010, época 2$gv. 14, no. 41, p. 13-16
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INIA Tacuarembó (TBO) |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha actual : |
17/04/2017 |
Actualizado : |
11/10/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
A - A |
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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