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Fitness landscapes for predicting evolution between environments

datacite.subject.fosCiências Naturaispt_PT
dc.contributor.advisorBank, Claudia
dc.contributor.authorGhenu, Ana-Hermina
dc.date.accessioned2023-12-29T11:46:09Z
dc.date.available2023-12-29T11:46:09Z
dc.date.issued2023-11-23
dc.date.submitted2023-11
dc.description.abstractPrediction of evolution is an ambitious undertaking that would consolidate knowledge from all fields of biology for the benefit of global health and biodiversity. Although prediction has been a foundational goal of population genetics theory, this goal is obstructed by the common simplifying assumptions of absent or weak genetic interactions (G⇥G), gene-by-environment interac tions (G⇥E), and higher-order epistasis-by-environment inter actions (G⇥G⇥E). This thesis examines the challenges posed by genetic and environmental interactions to the goal of predict ing evolution. Fitness landscapes models are brought to bear on data from both wild populations and laboratory conditions in order to investigate the predictability of two pressing issues: species-level biodiversity and antibiotic resistance evolution.pt_PT
dc.identifier.tid101755708pt_PT
dc.identifier.urihttp://hdl.handle.net/10362/161729
dc.language.isoengpt_PT
dc.relationSFRH/BD/138215/2018pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectGeneticpt_PT
dc.subjectenvironmentpt_PT
dc.subjectevolutionpt_PT
dc.titleFitness landscapes for predicting evolution between environmentspt_PT
dc.typedoctoral thesis
dspace.entity.typePublication
person.familyNameGhenu
person.givenNameAna-Hermina
person.identifier.orcid0000-0002-9088-2232
rcaap.rightsopenAccesspt_PT
rcaap.typedoctoralThesispt_PT
relation.isAuthorOfPublication86aa105f-6a66-4771-9bf7-77737b961d17
relation.isAuthorOfPublication.latestForDiscovery86aa105f-6a66-4771-9bf7-77737b961d17
thesis.degree.nameThesis presented to obtain the Ph.D degree in Integrative Biology & Biomedicinept_PT

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