Molecular Phylogenetics

Prerequisites

This course will provide training for bench-based biologists to use molecular data to construct and interpret phylogenies, and test their hypotheses. Delegates will gain hands-on practice of using a variety of programs freely-available online and commonly used in molecular studies, interspersed with some lectures.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
• Please be aware that these courses are only free for University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here
• Further details regarding eligibility criteria are available here

• Limited knowledge of the field of molecular evolution
• Some experience of examining DNA/protein sequence data

Number of sessions: 3

Bioinformatics, Data handling, Data mining, Data visualisation, Phylogenetics

After this course you should be able to:

• Reconstruct your own trees from data, choosing an appropriate set of tools and models
• Have an overview of the software available for phylogenetic reconstruction
• Know about the advantages and disadvantages of different phylogenetic reconstruction methods and make an informed choice
• Know how to interpret the results with regards to evolutionary information, robustness and potential inaccuracies

During this course you will learn about:

• The principles of phylogenetics and how to reconstruct phylogenetic trees from molecular data
• The different methods for phylogenetic reconstruction: distance-based, maximum likelihood, Bayesian
• How to interpret reconstructed trees and assess their robustness
• How to test hypotheses with respect to trees and decide which model to use for tree inference
• Statistical methods to detect positive selection in coding sequences
• How to use Bayesian methods for divergence time estimation

Presentations, demonstrations and practicals

• Free for University of Cambridge students
• £ 50/day for all University of Cambridge staff, including postdocs, and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 100/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

3 days

Once a year