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In silico analysis of Pinus L. Chloroplast DNA to microsatellites regions
(2019-01-01)
The Pinus genus covers a wide variety of widely cultivated species due to adaptability, high growth and wood quality. Molecular markers have been used for many genetic analyses, and among them, the microsatellite markers ...
In silico analysis of Simple Sequence Repeats from chloroplast genomes of Solanaceae species
(BRAZILIAN SOC PLANT BREEDING, 2009)
The availaibilty of chloroplast genome (cpDNA) sequences of Atropa belladonna, Nicotiana sylvestris, N tabacum, N tomentosiformis, Solanum bulbocastanum, S lycopersicum and S tuberosum, which are Solanaceae species, allowed ...
Development and characterization of SSR markers for Trichloris crinita using sequence data from related grass speciesDesarrollo y caracterización de marcadores moleculares SSR para Trichloris crinita usando secuencias de gramíneas filogenéticamente cercanas
(Universidad Nacional de Cuyo, 2018-05)
Trichloris crinita es una importante gramínea forrajera, nativa de regiones áridas del continente americano. A pesar de su importancia, no existen herramientas moleculares ni secuencias nucleotídicas disponibles para esta ...
Spatial genetic structure of Hymenaea stigonocarpa Mart. ex Hayne assessed with chloroplast microsatellite markers
(IPEF-INST PESQUISAS ESTUDOS FLORESTAIS, 2009)
The use of chloroplast DNA markers (cpDNA) helps to elucidate questions related to ecology, evolution and genetic structure. The knowledge of inter-and intra-population genetic structure allows to design effective conservation ...
Marker-trait Association for Resistance to Sugarcane Mosaic Virus (SCMV) in a Sugarcane (Saccharum spp.) Panel
(2022-01-01)
Sugarcane mosaic disease (SMD) caused by sugarcane mosaic virus, is one of the main diseases in sugarcane production areas in Brazil. Thus, the identification of new sources of resistance for use in future introgression ...
Images sub-segmentation with the PFCM clustering algorithm
(2009)
In this work we propose a method for subsegmentation of images using the PFCM clustering algorithm. The sub-segmentation consists of finding, within the clusters found using the segmentation process, those data less ...