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Registro Completo |
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Biblioteca(s): |
Embrapa Acre; Embrapa Amapá; Embrapa Amazônia Oriental. |
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Data corrente: |
14/10/2019 |
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Data da última atualização: |
27/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SCHEPASCHENKO, D.; CHAVE, J.; PHILLIPS, O. L.; LEWIS, S. L.; DAVIES, S. J.; RÉJOU-MÉCHAIN, M.; SIST, P.; SCIPAL, K.; PERGER, C.; HERAULT, B.; LABRIÈRE, N.; HOFHANSL, F.; AFFUM-BAFFOE, K.; ALEINIKOV, A.; ALONSO, A.; AMANI, C.; ARAUJO-MURAKAMI, A.; ARMSTON, J.; ARROYO, L.; ASCARRUNZ, N.; AZEVEDO, C. P. de; BAKER, T.; BALAZY, R.; BEDEAU, C.; BERRY, N.; BILOUS, A. M.; BIOLUS, S. Y.; BISSIENGOU, P.; BLANC, L.; BOBKOVA, K. S.; BRASLAVSKAYA, T.; BRIENEN, R.; BURSLEM, D. F. R. P.; CONDIT, R.; CUNI-SANCHEZ, A.; DANILINA, D.; TORRES, D. del C.; DERROIRE, G.; DESCROIX, L.; SOTTA, E. D.; OLIVEIRA, M. V. N. d'; DRESEL, C.; ERWIN, T.; EVDOKIMENKO, M. D.; FALCK, J.; FELDSPAUSCH, T. R.; FOLI, E. G.; FOSTER, R.; FRITZ, S.; GARCIA-ABRIL, A. D.; GORNOV, A.; GORNOVA, M.; GOTHARD-BASSÉBÉ, E.; GOURLET-FLEURY, S.; GUEDES, M. C.; HAMER, K. C.; SUSANTY, F. H.; HIGUCHI, N.; CORONADO, E. N. H.; HUBAU, W.; HUBBELL, S.; ILSTEDT, U.; IVANOV, V. V.; KANASHIRO, M.; KARLSSON, A.; KARMINOV, V. N.; KILLEEN, T.; KOFFI, J. C. K.; KONOVALOVA, M.; KRAXNER, F.; KREJZA, J.; KRISNAWATI, H.; KRIVOBOKOV, L. V.; KUZNETSOV, M. A.; LAKYDA, I.; LAKYDA, P. I.; LICONA, J. C.; LUCAS, R. M.; LUKINA, N.; LUSSETTI, D.; MALHI, Y.; MANZANERA, J. A.; MARIMON, B.; MARIMON JUNIOR, B. H.; VASQUEZ MARTINEZ, R.; MARTYNENKO, O. V.; MATSALA, M.; MATYASHUK, R. K.; FREITAS, L. J. M. de; MEMIAGHE, H.; MENDONZA, C.; MONTEAGUDO MENDONZA, A.; MOROZIUK, O. V.; MUKHORTOVA, L.; MUSA, S.; NAZIMOVA, D. I.; OKUDA, T.; OLIVEIRA, L. C. de; ONTIKOV, P. V.; OSIPOV, A. F.; PIETSCH, S.; PLAYFAIR, M.; POULSEN, J.; RADCHENKO, V. G.; RODNEY, K.; ROZAK, A. H.; RUSCHEL, A. R.; RUTISHAUSER, E.; SEE, L.; SHCHEPASHCHENKO, M.; SHEVCHENKO, N.; SHVIDENKO, A.; SILVEIRA, M.; SINGH, J.; SONKÉ, B.; SOUZA, C. R. de; STERENCZAK, K.; STONOZHENKO, L.; SULLIVAN, M. J. P; SZATNIEWSKA, J.; TAEDOUMG, H.; STEEGE, H. ter; TIKHONOVA, E.; TOLEDO, M.; TREFILOVA, O. V.; VALBUENA, R.; VALENZUELA GAMARRA, L.; VASILIEV, S.; VEDROVA, E. F.; VERHOVETS, S. V.; VIDAL, E.; VLADIMIROVA, N. A.; VLEMINCKX, J.; VOS, V. A.; VOZMITEL, F. K.; WANEK, W.; WEST, T. A. P.; WOELL, H.; WOODS, J. T.; WORTEL, V.; YAMADA, T.; HAJAR, Z. S. N.; ZO-BI, I. C. |
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Afiliação: |
Dmitry Schepaschenko, International Institute for Applied Systems Analysis, Laxenburg, Austria/Bauman Moscow State Technical University, Mytischi, Russia; Jérôme Chave, Laboratoire Evolution et Diversité Biologique CNRS/Université Paul Sabatier, Toulouse, France; Oliver L. Phillips, University of Leeds, Leeds, UK/University College London, London.; Simon L. Lewis, University of Leeds, Leeds, UK/University College London, London.; Stuart J. Davies, Forest Global Earth Observatory, Smithsonian Tropical Research Institute, Washington.; Maxime Réjou-Méchain, AMAP, IRD, CNRS, CIRAD, INRA, University Montpellier, Montpellier, France.; Plinio Sist, CIRAD, Montpellier, France/Univ Montpellier, CIRAD, Montpellier, France.; Klaus Scipal, European Space Agency, ESTEC, Noordwijk, The Netherlands.; Christoph Perger, International Institute for Applied Systems Analysis, Laxenburg, Austria/Spatial Focus GmbH, Vienna, Austria.; Bruno Herault, CIRAD, Montpellier, France/Univ Montpellier, CIRAD, Montpellier, France/Institut National Polytechnique Félix Houphouët-Boigny, Côte d’Ivoire; Nicolas Labrière, Université Paul Sabatier, Toulouse, France.; Florian Hofhansl, International Institute for Applied Systems Analysis, Laxenburg, Austria.; Kofi Affum-Baffoe, Mensuration Unit, Forestry Commission of Ghana, Kumasi, Ghana.; Alexei Aleinikov, Russian Academy of Sciences, Moscow, Russia.; Alfonso Alonso, Smithsonian Conservation Biology Institute, Washington, DC.; Christian Amani, Centre for International Forestry Research (CIFOR), Bogor, Indonesia.; Alejandro Araujo-Murakami, Universidad Autonoma Gabriel Rene Moreno, Santa Cruz, Bolivia.; John Armston, University of Maryland, USA/University of Queensland, Brisbane, Australia.; Luzmila Arroyo, Universidad Autónoma Gabriel Rene Moreno, Santa Cruz, Bolivia.; Nataly Ascarrunz, Instituto Boliviano de Investigacion Forestal (IBIF), Casilla, Bolivia.; CELSO PAULO DE AZEVEDO, CPAA; Timothy Baker, University of Leeds, Leeds, UK.; Radomir Balazy, Forest Research Institute, Poland.; Caroline Bedeau, ONF-Réserve de Montabo Cayenne Cedex, Cayenne, French Guiana.; Nicholas Berry, The Landscapes and Livelihoods Group, Edinburgh, UK.; Andrii M. Bilous, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.; Svitlana Yu. Bilous, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.; Pulchérie Bissiengou, Herbier National du Gabon (IPHAMETRA), Libreville, Gabon.; Lilian Blanc, CIRAD, Montpellier, France/Univ Montpellier, Montpellier, France.; Kapitolina S. Bobkova, Ural Branch of Russian Academy of Sciences, Syktyvkar, Russia.; Tatyana Braslavskaya, Russian Academy of Sciences, Moscow, Russia.; Roel Brienen, University of Leeds, Leeds, UK.; David F. R. P. Burslem, University of Aberdeen, Aberdeen, UK.; Richard Condit, Morton Arboretum, Lisle, IL, USA.; Aida Cuni-Sanchez, University of York, Heslington, York, UK.; Dilshad Danilina, V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, Russia.; Dennis del Castillo Torres, Instituto de Investigaciones de la Amazonía Peruana, Iquitos, Peru.; Géraldine Derroire, CIRAD, UMR EcoFoG, France, French Guiana.; Laurent Descroix, ONF-Réserve de Montabo Cayenne Cedex, Cayenne, French Guiana.; ELENEIDE DOFF SOTTA, CPAF-AP; MARCUS VINICIO NEVES D OLIVEIRA, CPAF-AC; Christopher Dresel, International Institute for Applied Systems Analysis, Laxenburg, Austria/Spatial Focus GmbH, Vienna, Austria.; Terry Erwin, Smithsonian Institution, Washington, DC.; Mikhail D. Evdokimenko, V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, Russia.; Jan Falck, The Swedish University of Agricultural Sciences, Umeå, Sweden.; Ted R. Feldpausch, University of Exeter, Exeter, UK.; Ernest G. Foli, Forestry Research Institute of Ghana, Kumasi, Ghana.; Robin Foster, The Field Musium, Chicago, IL, USA.; Steffen Fritz, International Institute for Applied Systems Analysis, Laxenburg, Austria.; Antonio Damian Garcia-Abril, Universidad Politecnica de Madrid, Madrid, Spain.; Aleksey Gornov, Center of Forest Ecology and Productivity of the Russian Academy of Sciences, Moscow, Russia.; Maria Gornova, Center of Forest Ecology and Productivity of the Russian Academy of Sciences, Moscow, Russia.; Ernest Gothard-Bassébé, Institut Centrafricain de Recherche Agronomique (ICRA), Bangui, Central African Republic.; Sylvie Gourlet-Fleury, CIRAD, Montpellier, France/Univ Montpellier, CIRAD, Montpellier, France.; MARCELINO CARNEIRO GUEDES, CPAF-AP; Keith C. Hamer, University of Leeds, Leeds, UK.; Farida Herry Susanty, Forestry and Environment Research Development and Innovation Agency (FOERDIA), Bogor, Indonesia.; Niro Higuchi, Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil.; Eurídice N. Honorio Coronado, Instituto de Investigaciones de la Amazonía Peruana, Iquitos, Peru.; Wannes Hubau, University of Leeds, Leeds, UK/Ghent University, Ghent, Belgium.; Stephen Hubbell, University of California, Los Angeles, CA, USA.; Ulrik Ilstedt, The Swedish University of Agricultural Sciences, Umeå, Sweden.; Viktor V. Ivanov, V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, Russia.; MILTON KANASHIRO, CPATU; Anders Karlsson, The Swedish University of Agricultural Sciences, SLU, Umeå, Sweden.; Viktor N. Karminov, Russian Academy of Sciences, Moscow, Russia.; Timothy Killeen, World Wildlife Fund, Santa Cruz de la Sierra, Bolivia.; Jean-Claude Konan Koffi, Sodefor, Abidjan, Côte d’Ivoire.; Maria Konovalova, V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, Russia.; Florian Kraxner, International Institute for Applied Systems Analysis, Laxenburg, Austria.; Jan Krejza, Global Change Research Institute CAS, Brno, Czech Republic.; Haruni Krisnawati, Forestry and Environment Research Development and Innovation Agency (FOERDIA), Bogor, Indonesia.; Leonid V. Krivobokov, V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, Russia.; Mikhail A . Kuznetsov, Institute of Biology, Komi Scientific Center, Ural Branch of Russian Academy of Sciences, Syktyvkar, Russia.; Ivan Lakyda, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.; Petro I. Lakyda, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.; Juan Carlos Licona, Instituto Boliviano de Investigacion Forestal (IBIF), Casilla, Bolivia.; Richard M. Lucas, Aberystwyth University, Aberystwyth, UK.; Natalia Lukina, Russian Academy of Sciences, Moscow, Russia.; Daniel Lussetti, The Swedish University of Agricultural Sciences, Umeå, Sweden.; Yadvinder Malhi, University of Oxford, Oxford, UK.; José Antonio Manzanera, Universidad Politecnica de Madrid, Madrid, Spain.; Beatriz Marimon, Universidade do Estado de Mato Grosso (UNEMAT), Nova Xavantina, Mato Grosso, Brazil.; Ben Hur Marimon Junior, Universidade do Estado de Mato Grosso (UNEMAT), Nova Xavantina, Mato Grosso, Brazil.; Rodolfo Vasquez Martinez, Universidad Nacional de San Antonio Abad del Cusco, Oxapampa, Peru.; Olga V. Martynenko, Russian Institute of Continuous Education in Forestry, Pushkino, Russia.; Maksym Matsala, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.; Raisa K. Matyashuk, Institute for Evolutionary Ecology of the National Academy of Sciences of Ukraine, Kyiv, Ukraine.; LUCAS JOSE MAZZEI DE FREITAS, CPATU; Hervé Memiaghe, University of Oregon, Eugene, OR, USA.; Casimiro Mendoza, Forest Management in Bolivia, Sacta, Bolivia.; Abel Monteagudo Mendoza, Universidad Nacional de San Antonio Abad del Cusco, Oxapampa, Peru.; Olga V. Moroziuk, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.; Liudmila Mukhortova, V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, Russia.; Samsudin Musa, Forest Reserach Institute of Malaysia (FRIM), Kuala Lumpur, Malaysia.; Dina I. Nazimova, V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, Russia.; Toshinori Okuda, Hiroshima University, Hiroshima, Japan.; LUIS CLAUDIO DE OLIVEIRA, CPAF-AC; Petr V. Ontikov, Bauman Moscow State Technical University, Mytischi, Russia.; Andrey F. Osipov, Russian Academy of Sciences, Syktyvkar, Russia; Stephan Pietsch, International Institute for Applied Systems Analysis, Laxenburg, Austria.; Maureen Playfair, Center for Agricultural research in Suriname, Paramaribo, Suriname.; John Poulsen, Nicholas School of the Environment, Duke University, Durham, USA.; Vladimir G. Radchenko, Institute for Evolutionary Ecology of the National Academy of Sciences of Ukraine, Kyiv, Ukraine.; Kenneth Rodney, The Iwokrama International Centre for Rain Forest Conservation and Development, Georgetown, Guyana.; Andes H. Rozak, Cibodas Botanic Gardens - Indonesian Institute of Sciences (LIPI), Cianjur, Indonesia.; ADEMIR ROBERTO RUSCHEL, CPATU; Ervan Rutishauser, Smithsonian Tropical Research Institute, Ancon, Panama.; Linda See, International Institute for Applied Systems Analysis, Laxenburg, Austria.; Maria Shchepashchenko, Russian Institute of Continuous Education in Forestry, Pushkino, Russia.; Nikolay Shevchenko, Center of Forest Ecology and Productivity of the Russian Academy of Sciences, Moscow, Russia.; Anatoly Shvidenko, International Institute for Applied Systems Analysis, Laxenburg, Austria/V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, Russia.; Marcos Silveira, Museu Universitário, Universidade Federal do Acre (Ufac), Rio Branco, Brazil.; James Singh, Guyana Forestry Commission, Kingston Georgetown, Guyana.; Bonaventure Sonké, Plant Systematic and Ecology Laboratory, University of Yaoundé I, Yaounde, Cameroon.; CINTIA RODRIGUES DE SOUZA, CPAA; Krzysztof Stere?czak, Forest Research Institute, Department of Geomatics, Raszyn, Poland.; Leonid Stonozhenko, Russian Institute of Continuous Education in Forestry, Pushkino, Russia.; Martin J. P. Sullivan, University of Leeds, Leeds, UK.; Justyna Szatniewska, Global Change Research Institute CAS, Brno, Czech Republic.; Hermann Taedoumg, University of Yaoundé I, Yaounde, Cameroon/Bioversity international, Yaoundé, Cameroun.; Hans ter Steege, Naturalis Biodiversity Center, Leiden, The Netherlands.; Elena Tikhonova, Center of Forest Ecology and Productivity of the Russian Academy of Sciences, Moscow, Russia.; Marisol Toledo, Museo de Historia Natural Noel Kempff Mercado, Universidad Autónoma Gabriel Rene Moreno, Santa Cruz, Bolivia.; Olga V. Trefilova, V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, Russia.; Ruben Valbuena, School of Natural Sciences, Bangor University, Bangor, United Kingdom.; Luis Valenzuela Gamarra, Jardín Botánico de Missouri; Universidad Nacional de San Antonio Abad del Cusco, Oxapampa, Peru.; Sergey Vasiliev, Bauman Moscow State Technical University, Mytischi, Russia.; Estella F. Vedrova, V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, Russia.; Sergey V. Verhovets, Siberian Federal University, Krasnoyarsk, Russia/Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia.; Edson Vidal, Luiz de Queiroz College of Agriculture, University of Sao Paolo, Piracicaba, Sa?o Paulo, Brazil.; Nadezhda A. Vladimirova, 7State Nature Reserve Denezhkin Kamen, Severouralsk, Russia.; Jason Vleminckx, Florida International University, Miami, FL, USA.; Vincent A. Vos, Universidad Autónoma del Beni, Riberalta, Bolivia.; Foma K. Vozmitel, Bauman Moscow State Technical University, Mytischi, Russia.; Wolfgang Wanek, University of Vienna, Vienna, Austria.; Thales A. P. West, New Zealand Forest Research Institute (Scion), Rotorua, New Zealand.; Hannsjorg Woell, Unaffiliated (retired), Bad Aussee, Austria.; John T. Woods, W.R.T College of Agriculture and Forestry, University of Liberia, Monrovia, Liberia.; Verginia Wortel, Center for Agricultural Research in Suriname, Paramaribo, Suriname.; Toshihiro Yamada, Hiroshima University, Higashi-Hiroshima, Hiroshima, Japan.; Zamah Shari Nur Hajar, Forest Research Institute of Malaysia M(FRIM), Kuala Lumpur, Malaysia.; Irié Casimir Zo-Bi, Institut National Polytechnique Félix Houphouët-Boigny, Yamoussoukro, Côte d’Ivoire. |
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Título: |
The Forest Observation System, building a global reference dataset for remote sensing of forest biomass. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Scientific Data, v. 6, n. 198, p. 1-11, 2019. |
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DOI: |
10.1038/s41597-019-0196-1 |
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Idioma: |
Inglês |
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Conteúdo: |
Forest biomass is an essential indicator for monitoring the Earth?s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world?s forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RSbased biomass products while developing new synergies between the RS and ground-based ecosystem research communities. |
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Palavras-Chave: |
Bases de datos; Biomasa aérea; Estudios de observación; Forest Observation System (FOS); Recursos forestales; Sistema de Observação Florestal; Teledetección. |
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Thesagro: |
Base de Dados; Biomassa; Floresta; Proteção Florestal; Sensoriamento Remoto. |
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Thesaurus Nal: |
Aboveground biomass; Databases; Forest resources; Observational studies; Remote sensing. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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024 7 $a10.1038/s41597-019-0196-1$2DOI
100 1 $aSCHEPASCHENKO, D.
245 $aThe Forest Observation System, building a global reference dataset for remote sensing of forest biomass.$h[electronic resource]
260 $c2019
520 $aForest biomass is an essential indicator for monitoring the Earth?s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world?s forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RSbased biomass products while developing new synergies between the RS and ground-based ecosystem research communities.
650 $aAboveground biomass
650 $aDatabases
650 $aForest resources
650 $aObservational studies
650 $aRemote sensing
650 $aBase de Dados
650 $aBiomassa
650 $aFloresta
650 $aProteção Florestal
650 $aSensoriamento Remoto
653 $aBases de datos
653 $aBiomasa aérea
653 $aEstudios de observación
653 $aForest Observation System (FOS)
653 $aRecursos forestales
653 $aSistema de Observação Florestal
653 $aTeledetección
700 1 $aCHAVE, J.
700 1 $aPHILLIPS, O. L.
700 1 $aLEWIS, S. L.
700 1 $aDAVIES, S. J.
700 1 $aRÉJOU-MÉCHAIN, M.
700 1 $aSIST, P.
700 1 $aSCIPAL, K.
700 1 $aPERGER, C.
700 1 $aHERAULT, B.
700 1 $aLABRIÈRE, N.
700 1 $aHOFHANSL, F.
700 1 $aAFFUM-BAFFOE, K.
700 1 $aALEINIKOV, A.
700 1 $aALONSO, A.
700 1 $aAMANI, C.
700 1 $aARAUJO-MURAKAMI, A.
700 1 $aARMSTON, J.
700 1 $aARROYO, L.
700 1 $aASCARRUNZ, N.
700 1 $aAZEVEDO, C. P. de
700 1 $aBAKER, T.
700 1 $aBALAZY, R.
700 1 $aBEDEAU, C.
700 1 $aBERRY, N.
700 1 $aBILOUS, A. M.
700 1 $aBIOLUS, S. Y.
700 1 $aBISSIENGOU, P.
700 1 $aBLANC, L.
700 1 $aBOBKOVA, K. S.
700 1 $aBRASLAVSKAYA, T.
700 1 $aBRIENEN, R.
700 1 $aBURSLEM, D. F. R. P.
700 1 $aCONDIT, R.
700 1 $aCUNI-SANCHEZ, A.
700 1 $aDANILINA, D.
700 1 $aTORRES, D. del C.
700 1 $aDERROIRE, G.
700 1 $aDESCROIX, L.
700 1 $aSOTTA, E. D.
700 1 $aOLIVEIRA, M. V. N. d'
700 1 $aDRESEL, C.
700 1 $aERWIN, T.
700 1 $aEVDOKIMENKO, M. D.
700 1 $aFALCK, J.
700 1 $aFELDSPAUSCH, T. R.
700 1 $aFOLI, E. G.
700 1 $aFOSTER, R.
700 1 $aFRITZ, S.
700 1 $aGARCIA-ABRIL, A. D.
700 1 $aGORNOV, A.
700 1 $aGORNOVA, M.
700 1 $aGOTHARD-BASSÉBÉ, E.
700 1 $aGOURLET-FLEURY, S.
700 1 $aGUEDES, M. C.
700 1 $aHAMER, K. C.
700 1 $aSUSANTY, F. H.
700 1 $aHIGUCHI, N.
700 1 $aCORONADO, E. N. H.
700 1 $aHUBAU, W.
700 1 $aHUBBELL, S.
700 1 $aILSTEDT, U.
700 1 $aIVANOV, V. V.
700 1 $aKANASHIRO, M.
700 1 $aKARLSSON, A.
700 1 $aKARMINOV, V. N.
700 1 $aKILLEEN, T.
700 1 $aKOFFI, J. C. K.
700 1 $aKONOVALOVA, M.
700 1 $aKRAXNER, F.
700 1 $aKREJZA, J.
700 1 $aKRISNAWATI, H.
700 1 $aKRIVOBOKOV, L. V.
700 1 $aKUZNETSOV, M. A.
700 1 $aLAKYDA, I.
700 1 $aLAKYDA, P. I.
700 1 $aLICONA, J. C.
700 1 $aLUCAS, R. M.
700 1 $aLUKINA, N.
700 1 $aLUSSETTI, D.
700 1 $aMALHI, Y.
700 1 $aMANZANERA, J. A.
700 1 $aMARIMON, B.
700 1 $aMARIMON JUNIOR, B. H.
700 1 $aVASQUEZ MARTINEZ, R.
700 1 $aMARTYNENKO, O. V.
700 1 $aMATSALA, M.
700 1 $aMATYASHUK, R. K.
700 1 $aFREITAS, L. J. M. de
700 1 $aMEMIAGHE, H.
700 1 $aMENDONZA, C.
700 1 $aMONTEAGUDO MENDONZA, A.
700 1 $aMOROZIUK, O. V.
700 1 $aMUKHORTOVA, L.
700 1 $aMUSA, S.
700 1 $aNAZIMOVA, D. I.
700 1 $aOKUDA, T.
700 1 $aOLIVEIRA, L. C. de
700 1 $aONTIKOV, P. V.
700 1 $aOSIPOV, A. F.
700 1 $aPIETSCH, S.
700 1 $aPLAYFAIR, M.
700 1 $aPOULSEN, J.
700 1 $aRADCHENKO, V. G.
700 1 $aRODNEY, K.
700 1 $aROZAK, A. H.
700 1 $aRUSCHEL, A. R.
700 1 $aRUTISHAUSER, E.
700 1 $aSEE, L.
700 1 $aSHCHEPASHCHENKO, M.
700 1 $aSHEVCHENKO, N.
700 1 $aSHVIDENKO, A.
700 1 $aSILVEIRA, M.
700 1 $aSINGH, J.
700 1 $aSONKÉ, B.
700 1 $aSOUZA, C. R. de
700 1 $aSTERENCZAK, K.
700 1 $aSTONOZHENKO, L.
700 1 $aSULLIVAN, M. J. P
700 1 $aSZATNIEWSKA, J.
700 1 $aTAEDOUMG, H.
700 1 $aSTEEGE, H. ter
700 1 $aTIKHONOVA, E.
700 1 $aTOLEDO, M.
700 1 $aTREFILOVA, O. V.
700 1 $aVALBUENA, R.
700 1 $aVALENZUELA GAMARRA, L.
700 1 $aVASILIEV, S.
700 1 $aVEDROVA, E. F.
700 1 $aVERHOVETS, S. V.
700 1 $aVIDAL, E.
700 1 $aVLADIMIROVA, N. A.
700 1 $aVLEMINCKX, J.
700 1 $aVOS, V. A.
700 1 $aVOZMITEL, F. K.
700 1 $aWANEK, W.
700 1 $aWEST, T. A. P.
700 1 $aWOELL, H.
700 1 $aWOODS, J. T.
700 1 $aWORTEL, V.
700 1 $aYAMADA, T.
700 1 $aHAJAR, Z. S. N.
700 1 $aZO-BI, I. C.
773 $tScientific Data$gv. 6, n. 198, p. 1-11, 2019.
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Registro original: |
Embrapa Amapá (CPAF-AP) |
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Classificação |
Cutter |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
06/12/2011 |
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Data da última atualização: |
24/01/2020 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
CINTRA, L. C. |
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Afiliação: |
LEANDRO CARRIJO CINTRA, CNPTIA. |
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Título: |
Computational investigations in eukaryotes genome de novo assembly using short reads. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
In: INTERNATIONAL CONFERENCE OF THE BRAZILIAN ASSOCIATION FOR BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 7.; INTERNATIONAL CONFERENCE OF THE IBEROAMERICAN SOCIETY FOR BIOINFORMATICS, 3., 2011, Florianópolis. Proceedings... Florianópolis: Associação Brasileira de Bioinformática e Biologia Computacional, 2011. |
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Páginas: |
Não paginado. |
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Idioma: |
Inglês |
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Notas: |
X-MEETING 2011. |
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Conteúdo: |
Recently news technologies in molecular biology enormously improved the sequencing data production, making it possible to generate billions of short reads totalizing gibabases of data per experiment. Prices for sequencing are decreasing rapidly and experiments that were impossible in the past because of costs are now being executed. Computational methodologies that were successfully used to solve the genome assembler problem with data obtained by the shotgun strategy, are now inefficient. Efforts are under way to develop new programs. At this moment, a stabilized condition for producing quality assembles is to use paired-end reads to virtually increase the length of reads, but there is a lot of controversy in other points. The works described in literature basically use two strategies: one is based in a high coverage[1] and the other is based in an incremental assembly, using the made pairs with shorter inserts first[2]. Independently of the strategy used the computational resources demanded are actually very high. Basically the present computational solution for the de novo genome assembly involves the generation of a graph of some kind [3], and one because those graphs use as node whole reads or k-mers, and considering that the amount of reads is very expressive; it is possible to infer that the memory resource of the computational system will be very important. Works in literature corroborate this idea showing that multiprocessors computational systems with at least 512 Gb of principal memory were used in de novo projects of eukaryotes [1,2,3]. As an example and benchmark source it is possible use the Panda project, which was executed by a research group consortium at China and generated de novo genome of the giant Panda (Ailuropoda melanoleura) . The project initially produced 231 Gb of raw data, which was reduced to 176 Gb after removing low-quality and duplicated reads. In the de novo assembly process just 134 Gb were used. Those bases were distributed in approximately 3 billions short reads. After the assembly, 200604 contigs were generated and 5701 multicontig scaffolds were obtained using 124336 contigs. The N50 was respectively . 36728 bp and 1.22 Mb for contigs and scaffolds. The present work investigated the computational demands of de novo assembly of eukaryotes genomes, reproducing the results of the Panda project. The strategy used was incremental as implemented in the SOAPdenovo software, which basically divides the assembly process in four steps: pre-graph to construction of kmer-graph; contig to eliminate errors and output contigs, map to map reads in the contigs and scaff to scaffold contigs. It used a NUMA (non-uniform memory access) computational system with 8 six-core processors with hyperthread tecnology and 512 Gb of RAM (random access memory), and the consumption of resources as memory and processor time were pointed for every steps in the process. The incremental strategy to solve the problem seems practical and can produce effective results. At this moment a work is in progress which is investigating a new methodology to group the short reads together using the entropy concept. It is possible that assemblies with better quality will be generated, because this methodology initially uses more informative reads. References [1] Gnerre et. al.; High-quality draft assemblies of mammalian genomes from massively parallel sequence data, Proceedings of the National Academy of Sciences USA, v. 108, n. 4, p. 1513-1518, 2010 [2] Li et. al.; The sequence and de novo assembly of the giant panda genome, Nature, v. 463, p. 311-317, 2010 [3] Schatz et. al.; Assembly of large genomes using second-generation sequencing, Genome Research, v. 20, p. 1165-1173, 2010 MenosRecently news technologies in molecular biology enormously improved the sequencing data production, making it possible to generate billions of short reads totalizing gibabases of data per experiment. Prices for sequencing are decreasing rapidly and experiments that were impossible in the past because of costs are now being executed. Computational methodologies that were successfully used to solve the genome assembler problem with data obtained by the shotgun strategy, are now inefficient. Efforts are under way to develop new programs. At this moment, a stabilized condition for producing quality assembles is to use paired-end reads to virtually increase the length of reads, but there is a lot of controversy in other points. The works described in literature basically use two strategies: one is based in a high coverage[1] and the other is based in an incremental assembly, using the made pairs with shorter inserts first[2]. Independently of the strategy used the computational resources demanded are actually very high. Basically the present computational solution for the de novo genome assembly involves the generation of a graph of some kind [3], and one because those graphs use as node whole reads or k-mers, and considering that the amount of reads is very expressive; it is possible to infer that the memory resource of the computational system will be very important. Works in literature corroborate this idea showing that multiprocessors computational systems with at least 512 G... Mostrar Tudo |
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Palavras-Chave: |
Bioinformática; Genomas de eucariotos. |
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Thesagro: |
Biologia Molecular; Genoma. |
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Thesaurus NAL: |
Bioinformatics; Eukaryotic cells; Genome; Molecular biology. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/49471/1/eukariotes.pdf
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Marc: |
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100 1 $aCINTRA, L. C.
245 $aComputational investigations in eukaryotes genome de novo assembly using short reads.$h[electronic resource]
260 $aIn: INTERNATIONAL CONFERENCE OF THE BRAZILIAN ASSOCIATION FOR BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 7.; INTERNATIONAL CONFERENCE OF THE IBEROAMERICAN SOCIETY FOR BIOINFORMATICS, 3., 2011, Florianópolis. Proceedings... Florianópolis: Associação Brasileira de Bioinformática e Biologia Computacional$c2011
300 $aNão paginado.
500 $aX-MEETING 2011.
520 $aRecently news technologies in molecular biology enormously improved the sequencing data production, making it possible to generate billions of short reads totalizing gibabases of data per experiment. Prices for sequencing are decreasing rapidly and experiments that were impossible in the past because of costs are now being executed. Computational methodologies that were successfully used to solve the genome assembler problem with data obtained by the shotgun strategy, are now inefficient. Efforts are under way to develop new programs. At this moment, a stabilized condition for producing quality assembles is to use paired-end reads to virtually increase the length of reads, but there is a lot of controversy in other points. The works described in literature basically use two strategies: one is based in a high coverage[1] and the other is based in an incremental assembly, using the made pairs with shorter inserts first[2]. Independently of the strategy used the computational resources demanded are actually very high. Basically the present computational solution for the de novo genome assembly involves the generation of a graph of some kind [3], and one because those graphs use as node whole reads or k-mers, and considering that the amount of reads is very expressive; it is possible to infer that the memory resource of the computational system will be very important. Works in literature corroborate this idea showing that multiprocessors computational systems with at least 512 Gb of principal memory were used in de novo projects of eukaryotes [1,2,3]. As an example and benchmark source it is possible use the Panda project, which was executed by a research group consortium at China and generated de novo genome of the giant Panda (Ailuropoda melanoleura) . The project initially produced 231 Gb of raw data, which was reduced to 176 Gb after removing low-quality and duplicated reads. In the de novo assembly process just 134 Gb were used. Those bases were distributed in approximately 3 billions short reads. After the assembly, 200604 contigs were generated and 5701 multicontig scaffolds were obtained using 124336 contigs. The N50 was respectively . 36728 bp and 1.22 Mb for contigs and scaffolds. The present work investigated the computational demands of de novo assembly of eukaryotes genomes, reproducing the results of the Panda project. The strategy used was incremental as implemented in the SOAPdenovo software, which basically divides the assembly process in four steps: pre-graph to construction of kmer-graph; contig to eliminate errors and output contigs, map to map reads in the contigs and scaff to scaffold contigs. It used a NUMA (non-uniform memory access) computational system with 8 six-core processors with hyperthread tecnology and 512 Gb of RAM (random access memory), and the consumption of resources as memory and processor time were pointed for every steps in the process. The incremental strategy to solve the problem seems practical and can produce effective results. At this moment a work is in progress which is investigating a new methodology to group the short reads together using the entropy concept. It is possible that assemblies with better quality will be generated, because this methodology initially uses more informative reads. References [1] Gnerre et. al.; High-quality draft assemblies of mammalian genomes from massively parallel sequence data, Proceedings of the National Academy of Sciences USA, v. 108, n. 4, p. 1513-1518, 2010 [2] Li et. al.; The sequence and de novo assembly of the giant panda genome, Nature, v. 463, p. 311-317, 2010 [3] Schatz et. al.; Assembly of large genomes using second-generation sequencing, Genome Research, v. 20, p. 1165-1173, 2010
650 $aBioinformatics
650 $aEukaryotic cells
650 $aGenome
650 $aMolecular biology
650 $aBiologia Molecular
650 $aGenoma
653 $aBioinformática
653 $aGenomas de eucariotos
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