B5791 - MOLECULAR PHYLOGENETICS

Learning outcomes

At the end of the course the student, starting from the knowledge of the mechanisms of molecular evolution, will be trained in the study of phylogenetic inference and will be able to reconstruct phylogenetic trees based on several molecular markers, applying the State-of-the-Art bioinformatic tools in the field. In particular the student will acquire the basics of phylogenomics and will analyze case studies in phylogenetics and phylogenomics.

Course contents

• orthology infererence and taxon sampling
• sequence alignement and filtering
• interpreting and comparing phylogenetic trees
• distance-based versus charcter-based inference algorythms
• MK models of molecular evolution
  
• maximum likelihood
  
• bayesian inference
• mixture models
• statistical support in phylogenies
• concatenation-based versus coalescence-based inferences
• gene tree correction and reconciliation on the species tree
• stochastic and systematic bias
• divergence times analyses
• modelling trait evolution on phylogenies: continuous traits
• modelling trait evolution on phylogenies: discrete traits
• inferring selection
• implementation of phylogenetics in bioinformatics pipeline
  

Readings/Bibliography

Together with the papers which we will discuss during the course, these free books are highly suggested:

 

• Phylogenetic Comparative Methods: Learning From Trees by Luke Harmon
• Phylogenetic Biology by Casey W. Dunn

Teaching methods

Each lesson will consist of a theoretical lecture followed by practical exercises.

Assessment methods

Written test, followed by an oral exam.

Teaching tools

Students will receive:

• the slides used during the in-person lectures on virtuale
• the materials for practical exercises on GitHub 

Office hours

See the website of Giobbe Forni