Sebastián Duchêne (Charles Perkins Centre, University of Sydney)
Friday 6th May, 2016
ESJ King Theatre, Medical Building, The University of Melbourne
Recent advances in sequencing technologies have dramatically increased the amount of available molecular data. Phylogenetic methods use statistical models to take advantage of these data to reconstruct the evolutionary history of organisms. For example, in the context of infectious diseases such methods allow inferences of time of origin, spread, and transmission rates. Typically, the reliability of these inferences is determined by comparing the statistical fit of a set of evolutionary models. However, this approach only informs about relative, but not absolute, model performance. As a result, it is impossible to determine the extent to which the inferences are accurate. In this talk, I will present an array of alternative approaches which assess the absolute performance of evolutionary models. Such assessments will allow us to improve the reliability of inferences made using current methods as well as develop more realistic models, thereby increasing the amount of information gained from genomic data sets.
Sebastián Duchêne is a postdoctoral fellow at the Charles Perkins Centre at the University of Sydney. His research involves evolutionary modeling of molecular data of viruses and bacteria. He has developed several methods to improve estimates of the evolutionary rates and timescales of these organisms. This work is key to make inferences about the time of origin of infectious outbreaks, changes in transmission rates over time, and adaptive evolution. Sebastián completed his PhD at the University of Sydney in 2015, supervised by Profs Simon Ho and Edward Holmes. He was recently awarded the 2016 D.G. Catcheside Prize from the Genetics Society of Australasia. In mid-2016 he will join Dr Kathryn Holt’s research group at the University of Melbourne as a McKenzie fellow.
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