Magdalena is from Bulgaria but did her Bachelor’s and integrated Master’s degree in University of Oxford. While there she studied Mathematics and Statistics but early on developed an interest in biological applications. Her Bachelor project explored network applications in epidemiology which was a stepping stone towards her internship in the Dutch Institute of Public Health where she worked on models of influenza vaccine effectiveness. During her Master’s Magdalena worked on two projects. The first one was on computational methods in biology with a focus on the models and tools to predict protein folding. The second one was on prediction methods in epidemiology with the RAPIDD Ebola Forecasting Challenge as a case study and a benchmark for evaluation of results. Before graduating she won a Laidlaw Scholarship for a project of her design and she used it to further her research in networks and biological modelling in the French institute of Public Health. To develop her interest in modelling, statistics and computational methods in biology, she has recently joined the Protein Evolution lab in Heidelberg University led by Prof. Rob Russell.

Abstract
This project aims to integrate the knowledge gathered through new practical research using more precise and advanced methods in structural biology, quantitative proteomics, cell biology, biochemistry and new technologies. In particular, it will scrutinize scilia and genetic variations within it which are expressed as a variety of observed phonotypical and hidden changes. Magdalena’s role in the context of the project is to look at the gathered data from a bioinformatics perspective and apply modelling and statistical techniques to identify patterns and therapeutic targets. All previously available data on ciliopathy mutations in aggregate with new experiments which have been completed as part of this ITN network will provide a rich database for statistical analysis. Expertise within the Protein Evolution group of Prof. Russell in terms of analytical techniques and tools such as the internally-developed socioaffinity method and Mechismo system provide the stepping stone for this bioinformatics project. Those methods will be adapted and used alongside the increasing knowledge of ciliopathy disease genes and mutations with the final aim of creating a schema of all possible complexes and interactions relevant to ciliary disease.