Christophe Ley - Directional statistics and protein bioinformatics: a flexible approach
|Starts:||14:00 24 Nov 2021|
|Ends:||15:00 24 Nov 2021|
|What is it:||Seminar|
|Organiser:||Department of Mathematics|
|Who is it for:||University staff, External researchers, Current University students|
Christophe Ley, Associate Professor of Statistics at the Department of Applied Mathematics, Computer Science and Statistics at Ghent University is our speaker for the Statistics seminar series.
Title: Directional statistics and protein bioinformatics: a flexible approach
Abstract: In the bioinformatics field, there has been a growing interest in modelling dihedral angles of amino acids by viewing them as data on the torus. This has motivated, over the past years, new proposals of distributions on the bivariate torus. The main drawback of most of these models is that the related densities are (pointwise) symmetric, despite the fact that the data usually present asymmetric patterns. This motivates the need to find a new way of constructing asymmetric toroidal distributions starting from a symmetric distribution. We tackle this problem in this paper by introducing the sine-skewed toroidal distributions. The general properties of the new models are presented. An important feature of our construction is that no normalizing constant needs to be calculated, leading to more flexible distributions without increasing the complexity of the models. The benefit of employing these new sine-skewed distributions is shown on the basis of protein data, where, in general, the new models outperform their symmetric antecedents. A word about Bayesian inference shall also be said, if the time permits it.
Organisation: Ghent University
Travel and Contact Information
Zoom link: https://zoom.us/j/92947173491