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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
28/10/2015 |
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Data da última atualização: |
19/02/2016 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
BAMBINI, M. D.; GIACHETTO, P. F.; FALCAO, P. R. K.; OLIVEIRA, F. S. de. |
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Afiliação: |
MARTHA DELPHINO BAMBINI, CNPTIA; POLIANA FERNANDA GIACHETTO, CNPTIA; PAULA REGINA KUSER FALCAO, CNPTIA; FERNANDA STRINGASSI DE OLIVEIRA, CNPTIA. |
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Título: |
Emerging biotechnologies: bioinformatics services applied to agriculture. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
In: CONGRESSO LATINO-IBEROAMERICANO DE GESTÃO DA TECNOLOGIA, 16., 2015, Porto Alegre. Inovação para além da tecnologia: anais. Porto Alegre: Universidade Federal do Rio Grande do Sul, 2015. |
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Páginas: |
Não paginado. |
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ISSN: |
2447-3340 |
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Idioma: |
Inglês |
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Notas: |
Altec 2015. |
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Conteúdo: |
Abstract - Bioinformatics is an emergent biotechnological field of study marked by interdisciplinarity and complexity. It involves the application and development of computational tools to biological data in order to process, generate, and disseminate biological knowledge. Bioinformatics is characterized by an intense generation of data and information (configured as a context of big data and e-science), associated with the need for computational resources with high processing and storage capacities and highly qualified and interdisciplinary staff, often found only in academia. The objective of this paper is to describe the organizational model and collaborative innovation activities of the Bioinformatics Multi-user Laboratory (LMB, in the acronym in Portuguese). The LMB is a facility located at the Brazilian Agricultural Research Corporation (Embrapa), the main Brazilian agricultural research public institute, formed by 46 Research and Service Centers distributed throughout Brazil and by several laboratories and business offices abroad, in America, Africa, Asia and Europe. Its mission involves to contribute to the advance of the frontier of knowledge in bioinformatics by: incorporating new technologies and enabling efficient solutions to the demands related to this field; providing access to high performance computing infrastructure and developing human skills. Considering the importance of biotechnology in the context of agricultural research, Embrapa implemented the LMB in 2011, with the purpose of increasing the efficiency of the use of computational, human and technological resources of Embrapa by providing access to bioinformatics computational resources, offering research collaboration possibilities and consultation on project design and biological data analysis. A case-study was conducted based on documentary research and interviews. The main findings of this research are: the description of the organizational model of LMB, the management team and roles; theservices it provides; its access policies and procedures of customer service. MenosAbstract - Bioinformatics is an emergent biotechnological field of study marked by interdisciplinarity and complexity. It involves the application and development of computational tools to biological data in order to process, generate, and disseminate biological knowledge. Bioinformatics is characterized by an intense generation of data and information (configured as a context of big data and e-science), associated with the need for computational resources with high processing and storage capacities and highly qualified and interdisciplinary staff, often found only in academia. The objective of this paper is to describe the organizational model and collaborative innovation activities of the Bioinformatics Multi-user Laboratory (LMB, in the acronym in Portuguese). The LMB is a facility located at the Brazilian Agricultural Research Corporation (Embrapa), the main Brazilian agricultural research public institute, formed by 46 Research and Service Centers distributed throughout Brazil and by several laboratories and business offices abroad, in America, Africa, Asia and Europe. Its mission involves to contribute to the advance of the frontier of knowledge in bioinformatics by: incorporating new technologies and enabling efficient solutions to the demands related to this field; providing access to high performance computing infrastructure and developing human skills. Considering the importance of biotechnology in the context of agricultural research, Embrapa implemented the LMB i... Mostrar Tudo |
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Palavras-Chave: |
Bioinformática; Genômica; Multiuser. |
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Thesagro: |
Agricultura; Pesquisa. |
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Thesaurus Nal: |
Agricultural research; Bioinformatics; Genomics. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/131921/1/altec2015.pdf
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Marc: |
LEADER 03008naa a2200289 a 4500
001 2027409
005 2016-02-19
008 2015 bl uuuu u00u1 u #d
022 $a2447-3340
100 1 $aBAMBINI, M. D.
245 $aEmerging biotechnologies$bbioinformatics services applied to agriculture.$h[electronic resource]
260 $c2015
300 $aNão paginado.
500 $aAltec 2015.
520 $aAbstract - Bioinformatics is an emergent biotechnological field of study marked by interdisciplinarity and complexity. It involves the application and development of computational tools to biological data in order to process, generate, and disseminate biological knowledge. Bioinformatics is characterized by an intense generation of data and information (configured as a context of big data and e-science), associated with the need for computational resources with high processing and storage capacities and highly qualified and interdisciplinary staff, often found only in academia. The objective of this paper is to describe the organizational model and collaborative innovation activities of the Bioinformatics Multi-user Laboratory (LMB, in the acronym in Portuguese). The LMB is a facility located at the Brazilian Agricultural Research Corporation (Embrapa), the main Brazilian agricultural research public institute, formed by 46 Research and Service Centers distributed throughout Brazil and by several laboratories and business offices abroad, in America, Africa, Asia and Europe. Its mission involves to contribute to the advance of the frontier of knowledge in bioinformatics by: incorporating new technologies and enabling efficient solutions to the demands related to this field; providing access to high performance computing infrastructure and developing human skills. Considering the importance of biotechnology in the context of agricultural research, Embrapa implemented the LMB in 2011, with the purpose of increasing the efficiency of the use of computational, human and technological resources of Embrapa by providing access to bioinformatics computational resources, offering research collaboration possibilities and consultation on project design and biological data analysis. A case-study was conducted based on documentary research and interviews. The main findings of this research are: the description of the organizational model of LMB, the management team and roles; theservices it provides; its access policies and procedures of customer service.
650 $aAgricultural research
650 $aBioinformatics
650 $aGenomics
650 $aAgricultura
650 $aPesquisa
653 $aBioinformática
653 $aGenômica
653 $aMultiuser
700 1 $aGIACHETTO, P. F.
700 1 $aFALCAO, P. R. K.
700 1 $aOLIVEIRA, F. S. de
773 $tIn: CONGRESSO LATINO-IBEROAMERICANO DE GESTÃO DA TECNOLOGIA, 16., 2015, Porto Alegre. Inovação para além da tecnologia: anais. Porto Alegre: Universidade Federal do Rio Grande do Sul, 2015.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Mandioca e Fruticultura. Para informações adicionais entre em contato com cnpmf.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Cocais; Embrapa Mandioca e Fruticultura. |
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Data corrente: |
25/04/2024 |
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Data da última atualização: |
07/05/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
SANTOS, V. da S.; PEREIRA, H. D.; ABREU, G. B.; SANTIAGO, C. M. |
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Afiliação: |
VANDERLEI DA SILVA SANTOS, CNPMF; HELCIO DUARTE PEREIRA; GUILHERME BARBOSA ABREU, CNPCA; CARLOS MARTINS SANTIAGO, CPACP. |
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Título: |
Evaluation and selection of cassava clones and exploitation of genetic covariance across multiple environments. |
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Ano de publicação: |
2024 |
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Fonte/Imprenta: |
Crop Science, 2024. |
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DOI: |
10.1002/csc2.21251 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Clonal evaluation trials of cassava (Manihot esculenta Crantz), where the main selection of this crop takes place, are usually carried out in multiple environments. This study investigated the influence of genotype–environment (GE) interaction on selection and how to explore genetic information across environments in a mixed model approach by modeling different genetic covariance structures. Approximately 240 cassava clones were assessed in an augmented block design during the 2020/2021 growing season in Brazil. The unstructured model was the best suited and used to investigate several strategies of selection. The predicted genetic gains based on individual analyses varied greatly among environments (5.52%–12.62% for root yield; 1.00%–6.09% for dry matter content; and 4.01%–9.42% for dry matter yield), although the clones mean was similar. Moreover, most of the selected clones in each environment outperformed the best check (>80%), except for root yield and dry matter yield in one environment. By multi-environment analysis, greater local gains were detected in each environment (means of 16.87% for root yield, 5.56% for dry matter content, and 17.27% for dry matter yield) and for mean heritability (0.52 for root yield, 0.76 for dry matter content, and 0.55 for dry matter yield). The coincidence of clones selected by individual and multi-environment analyses was 64% for root yield, 73% for dry matter content, and 66% for dry matter yield. The best scenario for selection is when all environments are considered simultaneously, for which regional genetic gains of 16.71% were predicted for root yield, 5.40% for dry matter content, and 17.06% for dry matter yield. MenosAbstract: Clonal evaluation trials of cassava (Manihot esculenta Crantz), where the main selection of this crop takes place, are usually carried out in multiple environments. This study investigated the influence of genotype–environment (GE) interaction on selection and how to explore genetic information across environments in a mixed model approach by modeling different genetic covariance structures. Approximately 240 cassava clones were assessed in an augmented block design during the 2020/2021 growing season in Brazil. The unstructured model was the best suited and used to investigate several strategies of selection. The predicted genetic gains based on individual analyses varied greatly among environments (5.52%–12.62% for root yield; 1.00%–6.09% for dry matter content; and 4.01%–9.42% for dry matter yield), although the clones mean was similar. Moreover, most of the selected clones in each environment outperformed the best check (>80%), except for root yield and dry matter yield in one environment. By multi-environment analysis, greater local gains were detected in each environment (means of 16.87% for root yield, 5.56% for dry matter content, and 17.27% for dry matter yield) and for mean heritability (0.52 for root yield, 0.76 for dry matter content, and 0.55 for dry matter yield). The coincidence of clones selected by individual and multi-environment analyses was 64% for root yield, 73% for dry matter content, and 66% for dry matter yield. The best scenario for select... Mostrar Tudo |
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Palavras-Chave: |
Manihot esculenta Crantz. |
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Thesagro: |
Genética; Mandioca. |
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Thesaurus NAL: |
Cassava; Manihot. |
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Categoria do assunto: |
--
A Sistemas de Cultivo |
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Marc: |
LEADER 02357naa a2200229 a 4500
001 2163917
005 2024-05-07
008 2024 bl uuuu u00u1 u #d
024 7 $a10.1002/csc2.21251$2DOI
100 1 $aSANTOS, V. da S.
245 $aEvaluation and selection of cassava clones and exploitation of genetic covariance across multiple environments.$h[electronic resource]
260 $c2024
520 $aAbstract: Clonal evaluation trials of cassava (Manihot esculenta Crantz), where the main selection of this crop takes place, are usually carried out in multiple environments. This study investigated the influence of genotype–environment (GE) interaction on selection and how to explore genetic information across environments in a mixed model approach by modeling different genetic covariance structures. Approximately 240 cassava clones were assessed in an augmented block design during the 2020/2021 growing season in Brazil. The unstructured model was the best suited and used to investigate several strategies of selection. The predicted genetic gains based on individual analyses varied greatly among environments (5.52%–12.62% for root yield; 1.00%–6.09% for dry matter content; and 4.01%–9.42% for dry matter yield), although the clones mean was similar. Moreover, most of the selected clones in each environment outperformed the best check (>80%), except for root yield and dry matter yield in one environment. By multi-environment analysis, greater local gains were detected in each environment (means of 16.87% for root yield, 5.56% for dry matter content, and 17.27% for dry matter yield) and for mean heritability (0.52 for root yield, 0.76 for dry matter content, and 0.55 for dry matter yield). The coincidence of clones selected by individual and multi-environment analyses was 64% for root yield, 73% for dry matter content, and 66% for dry matter yield. The best scenario for selection is when all environments are considered simultaneously, for which regional genetic gains of 16.71% were predicted for root yield, 5.40% for dry matter content, and 17.06% for dry matter yield.
650 $aCassava
650 $aManihot
650 $aGenética
650 $aMandioca
653 $aManihot esculenta Crantz
700 1 $aPEREIRA, H. D.
700 1 $aABREU, G. B.
700 1 $aSANTIAGO, C. M.
773 $tCrop Science, 2024.
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Embrapa Cocais (CPACP) |
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