Dr. Hajk-Georg Drost
Group Leader – Computational Biology
I am humbled by the vast variation of natural forms available on our planet. Today, I am among the lucky few that can devote time and resources to explore the molecular mechanisms generating this wondrous diversity as a hedge against natural selection.
My academic path was enabled by studying bioinformatics with a strong focus on statistical learning, machine learning, and predictive modeling with applications in comparative genomics and evolutionary transcriptomics. I obtained my BSc and MSc in Bioinformatics, and a PhD in Computer Science at the Institute of Computer Science – Martin-Luther University Halle, Germany where I studied natural variation through the lens of the developmental hourglass model with Ivo Grosse and Marcel Quint. New questions concerning the dynamics and epigenetic control of genomes led me to pursue a postdoc in the lab of Jerzy Paszkowski at the University of Cambridge, where I studied the epigenetic control of transposable elements and how these elements can generate natural variation in genomic landscapes. As a next step, I wanted to integrate my insights from evo-devo and (epi)-genomics research and joined the lab of Elliot Meyerowitz at the Sainsbury Laboratory in Cambridge. With Elliot, I sought to understand how regulatory changes during organ evolution in plants and animals can generate natural variants in organ morphology across diverse plant and animal species. Here, we were especially interested in the roles of lncRNAs and circRNAs in regulating these developmental processes.
After studying the mechanisms generating natural variation on different levels of organismal complexity, here at the Department of Molecular Biology, I now seek to understand how gene regulatory instructions are retained over evolutionary time to either conserve biological functions or diversify functions to enable the emergence of adaptive traits. For this attempt, I bring together a range of experts from mathematics, computer science, and bioinformatics backgrounds to develop the tools and methodologies to approach this question.
PhD Student – Algorithmic Bioinformatics
I studied computer science and mathematics at the University of Tübingen, Germany. Since 2013, I develop the protein sequence aligner Diamond, which was spurred by the challenges of handling the growing amounts of NGS data. In metagenomics studies, DNA is sequenced at terabase-scale from the entire microbial biosphere and needs to be computationally analyzed for remote evolutionary relationships. While traditional methods like NCBI BLAST required a supercomputer to be viable for such data, Diamond was the first tool to achieve a 20,000x speedup over BLAST for short read alignment in protein space and make this analysis accessible to any scientist. The tool has evolved over the years and is now widely used in metagenomics and phylogenomics applications.
In 2013, I won the U.S. Defense Threat Reduction Agency’s $1 Million Algorithm Challenge. This open competition involving over 3,000 researchers around the world awarded the best algorithm solution for rapidly and accurately characterising a complex clinical sample based on raw DNA sequence, an effort that contributed to the capabilities of the U.S. armed forces to diagnose and treat biothreats.
I specialized in high-performance and low-level programming in C++. My research is focused on enhancing Diamond, scaling its computational power and broadening its range of applications to address problems in phylogenomics.
Master Student – Gene Regulatory Network Evolution
I come from Bogotá, Colombia. I am currently coursing my masters in Bioinformatics in Wageningen University and I am interested in biological networks, metabolomics, synthetic biology and graph theory. I’ve started my internship at the Max Planck Institute for Developmental Biology and will be working with evolving gene regulatory networks. In my free time I like to read philosophy books, learning languages and trying new strange dishes with my friends.
My academic journey is currently encompassed by the study of bioinformatics and has specifically focused on systems biology, modeling dynamic systems and algorithm design. Before starting my masters, I acquired some work experience, mainly in the fields of education and automatized medical systems. My previous academic experience consisted of a bachelor’s degree in Biomedical Engineering, which I completed in Universidad de los Andes. After studying the details of biological network analysis in metabolomics and the mathematical models that allow the integration of multi-level biological processes, during my thesis at Wageningen University, I now will aim to contribute to the study of organ evolution in animals and plants through the study of the progression of gene regulatory networks during the differentiation process.