Computational Biology, Genomes and Evolution

To understand the vast complexity in biology, many research projects at the Vienna BioCenter have integrated algorithm development, modeling, and high-throughput processing of data. These computational tools enable the next-level analysis of large amounts of biological data, ranging from high-throughput microscopic images to genome sequences or thousands of single-cell transcriptomes, and are also indispensable for evolutionary biology research.

Computational biology has become the common thread that runs through all the Research Areas at the Vienna BioCenter. It involves developing and applying data-analytical and theoretical methods, mathematical modeling, and computational simulations to describe diverse biological functions at different spatial scales. Since the sequencing of the first whole genome in 1995, all major model organisms and hundreds of other species have had their genomes wholly or partially sequenced. This has led to genome-wide analyses becoming commonplace in many research institutions, and groups at the Vienna BioCenter use them extensively to study genomes (including their 3D organization), epigenomes, and transcriptomes. In turn, this has necessitated innovative strategies to process, analyze, and store the resulting datasets. Computational methods are also heavily used in biophysics, structural biology, and imaging at the Vienna BioCenter; for example, molecular dynamics uses computer simulations to model the structure of biomolecules and their interactions with the environment.