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Abstract
In recent years, high throughput technologies have led to an increase of datasets from omics disciplines allowing the understanding of the complex regulatory networks associated with biological processes. Leaf senescence is a complex mechanism controlled by multiple genetic and environmental variables, which has a strong impact on crop yield. Transcription factors (TFs) are key proteins in the regulation of gene expression, regulating different signaling [ver mas...]
dc.contributor.authorMoschen, Sebastian Nicolas
dc.contributor.authorHiggins, Janet
dc.contributor.authorDi Rienzo, Julio A.
dc.contributor.authorHeinz, Ruth Amelia
dc.contributor.authorPaniego, Norma Beatriz
dc.contributor.authorFernandez, Paula Del Carmen
dc.date.accessioned2017-09-05T11:51:18Z
dc.date.available2017-09-05T11:51:18Z
dc.date.issued2016
dc.identifier.issn1471-2105 (Online)
dc.identifier.otherhttps://doi.org/10.1186/s12859-016-1045-2
dc.identifier.urihttp://hdl.handle.net/20.500.12123/1122
dc.identifier.urihttps://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-016-1045-2?site=bmcbioinformatics.biomedcentral.com
dc.description.abstractIn recent years, high throughput technologies have led to an increase of datasets from omics disciplines allowing the understanding of the complex regulatory networks associated with biological processes. Leaf senescence is a complex mechanism controlled by multiple genetic and environmental variables, which has a strong impact on crop yield. Transcription factors (TFs) are key proteins in the regulation of gene expression, regulating different signaling pathways; their function is crucial for triggering and/or regulating different aspects of the leaf senescence process. The study of TF interactions and their integration with metabolic profiles under different developmental conditions, especially for a non-model organism such as sunflower, will open new insights into the details of gene regulation of leaf senescence.
dc.formatapplication/pdf
dc.language.isoeng
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceBMC Bioinformatics 17 (Suppl 5) :174 (June 2016)
dc.subjectGenética
dc.subjectAvejentamiento
dc.subjectGeneticseng
dc.subjectSenescenceeng
dc.subjectHojas
dc.subjectLeaveseng
dc.subjectHelianthus Annuus
dc.subject.otherGirasol
dc.titleNetwork and biosignature analysis for the integration of transcriptomic and metabolomic data to characterize leaf senescence process in sunflower
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.description.origenInst. de Biotecnología
dc.gic151887
dc.description.filFil: Moschen, Sebastian Nicolas. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.filFil: Higgins, Janet. Genome Analysis Centre, Norwich Research Park; Reino Unido
dc.description.filFil: Di Rienzo, Julio A.Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina
dc.description.filFil: Heinz, Ruth Amelia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.filFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.filFil: Fernandez, Paula Del Carmen. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina
dc.subtypecientifico


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