Computational Biology, Genomes and Evolution

How can innovative analyses be used to explore natural variation and uncover novel biological mechanisms?

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. 

Evolution is the unifying theory of the biological sciences: as Theodosius Dobzhansky put it, “nothing in biology makes sense except in the light of evolution”. Various aspects of evolutionary biology research are ongoing at the Vienna BioCenter, with one particular stronghold being the analysis of genomic and epigenomic variants to assess natural variation within and between populations. Such analyses provide insights into complex traits, adaptation, speciation,and evolutionary ecology (e.g., how competition between and within species has evolved). Some groups use comparative genomics to focus on the evolution of specific biological systems, such as biological clocks, hormone systems, or gene regulation.

Finally, the Mathematics and BioSciences Group and the Center for Integrative Bioinformatics Vienna develop mathematical methods and models that mimic the process of evolution.

Research Groups "Computational Biology, Genomes and Evolution"

Research Group Institute Topic
Berger GMI Chromatin Architecture and Function
Dolan GMI Development and Evolution of Land Plants
Mari-Ordonez GMI Mechanisms of recognition and silencing of transposons in plants
Nordborg GMI Population Genetics
Ramundo GMI Chloroplast biogenesis and protein quality control
Swarts GMI Tree-ring genomics
Brennecke IMBA Transposon silencing & heterochromatin formation by small RNAs
Burga IMBA Molecular determinants of biological idiosyncrasy
Elling IMBA Functional genomics in embryonic stem cells
Gerlich IMBA Chromosome structure and dynamics
Goloborodko IMBA Theoretical Models of Chromosome Structure
Jachowicz IMBA 'Dark' genome in early mammalian development
Rivron IMBA Blastoid development and implantation
Stark IMP Understanding transcriptional regulation
Tanaka IMP Molecular mechanisms of vertebrate regeneration
Campbell Max Perutz Labs Mechanisms that ensure chromosome segregation fidelity in mitosis
Hein Max Perutz Labs Systems Biology & Viruses
Hermisson Max Perutz Labs Mathematics and BioSciences Group (MaBS)
Menche Max Perutz Labs Quantitative Modelling of Biological Networks
Raible Max Perutz Labs Origin and Diversification of Hormone Systems
Ries Max Perutz Labs Super-resolution microscopy for structural cell biology
Swarts Max Perutz Labs Tree-ring genomics
Tessmar Max Perutz Labs Lunar periodicity and inner brain photoreceptors
von Haeseler Max Perutz Labs CIBIV - Center for Integrative Bioinformatics Vienna
Zagrovic Max Perutz Labs Molecular Biophysics
Baltazar de Lima de Sousa Uni Vienna - Faculty of Life Sciences Archaea Genome Evolution and Ecology
Golestani Uni Vienna - Faculty of Life Sciences Computational Modelling of Brain Function, Experimental Psycholinguistics and Psychophysics
Kuhlwilm Uni Vienna - Faculty of Life Sciences Evolutionary genomics
Mitteroecker Uni Vienna - Faculty of Life Sciences Theoretical and Evolutionary Biology
Pavlicev Uni Vienna - Faculty of Life Sciences Evolvability and Reproductive Biology
Revilla-i-Domingo Uni Vienna - Faculty of Life Sciences Early Animal Evolution, Stem Cell Differentiation & Deep-Sea Sponge Ecology
Rittmann Uni Vienna - Faculty of Life Sciences Archaea Physiology & Biotechnology
Simakov Uni Vienna - Faculty of Life Sciences Evolution of Metazoan Genome Architecture
Steiner Uni Vienna - Faculty of Life Sciences Mollusk Systematics
Technau Uni Vienna - Faculty of Life Sciences Molecular Evolution and Development
Waldherr Uni Vienna - Faculty of Life Sciences Computational Methods for Bio-/Chemical Processes
Weckwerth Uni Vienna - Faculty of Life Sciences Systems Theory in Ecology and Biology
Horn Uni Vienna - CeMESS Microbial Symbioses
Polz Uni Vienna - CeMESS Microbial Population Genomics & Microbial Viruses & Evolutionary Ecology & Microbiomes
Rattei Uni Vienna - CeMESS Computational and Systems Biology & Genome and Metagenome Analysis & HPC
Willemsen Uni Vienna - CeMESS Genomic evolution of giant viruses