Ágnes Jónás
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research interests:

I graduated as an Applied Mathematician at the University of Debrecen in Hungary. All along my university studies I was committed to practical research activities. Later I had the opportunity to get insights into bioinformatics, and I became very interested in its principles and associated tools that allow us to extract biologically interesting information from data.

In the course of my Ph.D., I am going to work on time series data coming from experimental evolution studies in Drosophila species. I will join to a project in which evolutionary trajectories of allele frequencies are modeled by using machine learning techniques such as Gaussian processes in order to understand SNP frequency changes over generations. For this, I will use whole-genome pool-seq data generated by Next Generation Sequencing (NGS) techniques. Pool-sequencing is a powerful method for estimating population-wide allele frequencies; however haplotype information of individual flies in the pool is lost. Therefore another aim of my Ph.D. is to reconstruct haplotypes from pool-seq data by applying statistical methods.