Alvin Meltsov

The nature of complex systems has always interested me. This interest guided me to study Biology at the University of Tartu. During my undergrad studies, I focused on cell biology and worked in a lab designing vectors to introduce point mutations to yeast helicase HMI1. After working in the laboratory for a year, I started to get into programming and statistics. Fascinated by the power of computational tools in biology and the emerging field of artificial intelligence, I decided to pivot towards bioinformatics.

As a bioinformatics analyst, I continued working on my interests at the Competence Centre on Health Technologies (CCHT), learning to use HPC environments for developing research and diagnostic pipelines. For my Bachelor's thesis, I explored non-invasive prenatal testing algorithms to find important genomic regions that could be targeted with a custom sequencing array. After finishing my thesis, I experimented with calculating polygenic risk scores from low coverage sequencing data accurately.

My studies continued at the Master's course of Computer Science at Tartu University, specialising in Data Science. I started working on transcriptional profiling methods and applying differential analysis (DE) on endometrial tissues from in vitro fertilisation (IVF) patients. Finally, I defended my Master's thesis on designing a non-iterative distance-based model for determining endometrial receptivity from a custom gene assay.

During my PhD, I plan to continue researching new models and tools for detecting pathologies or aberrations in the endometrium, hopefully contributing to increasing IVF success rate.