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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorTusscher, K.H.W.J. ten
dc.contributor.authorSaccheri, Jeroen
dc.date.accessioned2023-06-02T00:00:48Z
dc.date.available2023-06-02T00:00:48Z
dc.date.issued2023
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/43964
dc.description.abstractThis literature review discusses the intricate relationship between carbon (C) and nitrogen (N) in vascular plants. In order to grow and reproduce optimally, plants must maintain an internal balance between C and N while responding to changes in external availability. Although the C and N metabolic pathways are individually well-studied, mechanisms for regulating C and N levels are complex and multi-levelled, and several important details regarding how the C/N pathways interact to maintain balance are still unclear. This review examines how different fields in biology view the problem of resource allocation such as evolutionary biology, developmental biology and biophysics, using representative examples to show the strengths and weaknesses of each perspective. Furthermore, we highlight some key questions to be answered by each field to form a unifying picture of the system as a whole. The review concludes by suggesting that a combined approach is needed to inform future models, and gives some suggestions on what aspects of current perspectives present useful properties to be considered for such models. Special emphasis is given to the interpretation of signals, and a need for deeper inquiry into how a signalling molecule’s spatiotemporal dynamics and functional involvement in the C/N metabolic pathway can affect the potential information it carries to inform regulation processes.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectThis literature review how different fields of biology view the relationship between carbon (C) and nitrogen (N) in vascular plants, and discusses integrating perspectives to gain further insight into C/N balance.
dc.titleDeciding When and Where to Grow
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuBioinformatics and Biocomplexity
dc.thesis.id17141


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