BANK Claudia

  • Evolutionary Dynamics Group, Instituto Gulbenkian de Ciência, Oeiras, Portugal
  • Adaptation, Evolutionary Dynamics, Evolutionary Theory, Experimental Evolution, Hybridization / Introgression, Population Genetics / Genomics, Speciation
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I study evolution – and in particular, the population genetics of adaptation and speciation – at the interface between theoretical and empirical biology. The approaches I use involve theoretical modeling, computational methods, and statistical data analysis.

One of the major challenges in evolutionary biology is to investigate the processes and mechanisms by which populations adapt to their environment. To this end, novel experimental approaches and advances in biotechnology provide us with data sets of unprecedented type, size, and resolution, for which new analytical approaches and tools are in high demand. The aim of my group’s research is to shed light on the prevalence and evolutionary role of genetic interactions, and the relative importance of evolutionary forces during rapid adaptation to new environments ­ two questions of major interest both within the evolutionary community and with respect to the dangers to human health that are imposed by drug­resistance evolution and cancer. Our work stands out by the combination of three approaches: (1) We design straightforward and robust mathematical models in order to develop predictions and testable hypotheses regarding the interaction of evolutionary forces. (2) We develop statistical and computational methods that can handle complex new data sets, and assess the statistical power of new experimental approaches. (3) We evaluate hypotheses from evolutionary theory in the light of the information that we extract from large genomic data sets.

Coming from an undergraduate (combined Bachelor and Master’s) background in mathematics and physics, I discovered my passion for evolution through biophysics and biomathematics classes, which led me to do a PhD in the framework of the “Vienna Graduate School of Population Genetics” under the supervision of Joachim Hermisson, where I worked on speciation models. As part of my PhD studies, I spent a semester abroad in Mark Kirkpatrick’s lab at UT Austin. To continue my transition into biology after my PhD by getting my hands on empirical data, I chose to join Jeff Jensen’s lab at the EPFL as a postdoc. In particular, this gave me the chance to apply my modeling expertise to experimental-evolution data collected in Dan Bolon’s lab at UMass. In 2014, I spent one semester at UC Berkeley as a Simons fellow in the program “Evolutionary Biology and the Theory of Computing”. Since January 2016, I have been heading the Evolutionary Dynamics lab at the Gulbenkian Institute.

1 recommendation

Fisher's geometrical model and the mutational patterns of antibiotic resistance across dose gradients
Noémie Harmand, Romain Gallet, Roula Jabbour-Zahab, Guillaume Martin, Thomas Lenormand

Recommended by Inês Fragata and Claudia Bank
What doesn’t kill us makes us stronger: can Fisher’s Geometric model predict antibiotic resistance evolution?

The increasing number of reported cases of antibiotic resistance is one of today’s major public health concerns. Dealing with this threat involves understanding what drives the evolution of antibiotic resistance and investigating whether we can predict (and subsequently avoid or circumvent) it [1].
One of the most illustrative and common models of adaptation (and, hence, resistance evolution) is Fisher’s Geometric Model (FGM). The original model maps phenotypes to fitness, meaning that ea...


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