AET16

Applied Evolutionary Theory

A hands-on introduction to creating and analyzing models of evolution
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   IMPORTANT DATES for this Course
   Deadline for applications: Oct 31st 2016
   Course dates: Nov 7th - Nov 11th 2016

Candidates with adequate profile will be accepted in the next 72 hours after the application until we reach 20 participants.

Instructors:

Claudia Bank is heading the Evolutionary Dynamics group at the Instituto Gulbenkian de Ciência in Oeiras, Portugal. She studies adaptation and speciation at the interface between theoretical and empirical biology using a combination of theoretical modeling, computational methods, and statistical data analysis.
Coming from a undergraduate background in mathematics and physics, Claudia did her PhD in the framework of the “Vienna Graduate School of Population Genetics” working on speciation models with Joachim Hermisson, and, during a short-term scholarship at UT Austin, with Mark Kirkpatrick. As a postdoc in Jeff Jensen's lab at the Ecole Polytechnique Fédérale de Lausanne, she applied her modeling expertise to the a nalysis and interpretation of experimental-evolution data. As a 'dry' lab, work of the Evolutionary Dynamics Group is not restricted to a particular organism, scale of observation, or experimental method. Current projects involve experimental-evolution data from Escherichia coli, Saccharomyces cerevisiae, influenza A virus, and Drosophila, and data from natural populations of Formica ants. Using various mathematical, statistical, and computational tools, and complemented by targeted collaborations with 'wet' lab researchers, Claudia's work is dominated by questions about the prevalence and importance of epistatic interactions, the architecture of adaptation to challenging environments, and the predictability of evolution. Please check the website of Claudia's research group on Evolutionary Dynamics

Affiliation: Instituto Gulbenkian de Ciência, Oeiras, PT

Rafael Guerrero is a population geneticist working in the Department of Biology at Indiana University, Bloomington (USA). In his research, he uses a combination of computational and theoretical approaches to understand the role of genome structure and gene regulation in processes of population divergence.
Rafael did his doctoral work at the University of Texas at Austin, where he developed coalescent models for locally adapted chromosome inversions that provide a statistical foundation for population genomic studies. As a postdoctoral fellow, he has used transcriptomic and genomic data to research the evolution of reproductive barriers and regulatory divergence. He has studied a variety of systems -from malaria mosquitoes and tree frogs to tomatoes and wildflowers - inferring and quantifying evolutionary forces in natural populations through statistical tools such as likelihood maximization and Bayesian methods.

Affiliation: Indiana University, Bloomington, IN, USA

Jan Engelstädter is an evolutionary biologist based at The University of Queensland in Brisbane, Australia. He is broadly interested in the evolutionary biology of sexual processes, parasitism, and the interplay between these phenomena. His group uses a combination of mathematical modelling and experimental work to address fundamental questions within this exciting field. Jan did his PhD at University College London, working with Greg Hurst on the evolution of reproductive parasites such as the infamous bacterium Wolbachia. Following a short postdoc at Harvard University with David Haig, he did another postdoc with Sebastian Bonhoeffer at ETH Zurich where, in 2011, he also became a junior group leader. In 2012 is started a position at The University of Queensland where he is currently an ARC Future Fellow and Senior Lecturer. Current projects in which Jan's lab is involved include the evolution of gene exchange in bacteria, the evolution of antibiotic resistance, recombination rate evolution during speciation, and the evolution of asexual reproduction in animals. For more information, please visit Jan's lab website.

Affiliation: The University of Queensland, Brisbane, AU
Training Assistants from the IGC: Ana-Hermina Ghenu, Inês Fragata, and Alexandre Blanckaert

Course Description

For much of its history, our knowledge of evolution has been based heavily on theoretical models and hypotheses. In the age of novel experimental and technological approaches, we are now increasingly able to evaluate this theory; however, the basics of how and why to develop and analyze a simple model are often forgotten in the process of NGS analysis. This course aims at training evolutionary biologists in classical modeling and teach them ways to approach their own research questions through evolutionary theory.
Primarily through interactive hands-on sessions, complemented by an introduction to the cornerstones of modeling and its application to data analysis, this course will familiarize the participants with ways of approaching a research question with a simple model, and different strategies at gaining insight from the model. In groups of two, course participants will develop and analyze their own toy model in the course and present their findings to the group on the last day.
Topics that will be covered in the course include the following:
  • Why and how are models useful?
  • How to write down/develop a model
  • How simple/complicated should a model be?
  • Which modeling approach/programming language should I use for my question?
  • How to nail down a question with a model
  • Extracting results from an equation/simulation
  • How to evaluate a model using empirical data
Participants can use their preferred programming language during the hands-on sessions, and free access to Wolfram Mathematica will be provided. The instructors have modeling experience using Mathematica, R, Python, and C++.

Target audience

This course is targeted at evolutionary biologists with little or no explicit training in evolutionary modeling, who are interested in adding modeling approaches to their repertoire.

Pre-requisites

Programming experience with R, Python, C++, or Mathematica is helpful but not necessary. Participants with little or no programming experience are strongly advised to attend the optional free sessions providing an introduction to Mathematica and to reproducible modeling in the afternoon of the first day (Monday, Nov 6th at 2:30PM).

Detailed Program

Support

     

Instituto Gulbenkian de Ciência,

Apartado 14, 2781-901 Oeiras, Portugal

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Last updated:  Oct 25th 2016