EuroVis 2013 Keynote Speaker: Peter Stadler, University of Leipzig
Abstract: RNA has long been considered a boring intermediate between DNA, the genomic storage device, and proteins performing nearly all important functions in the cell. With the advent of high throughput sequencing and the technical capability of unbiased and reasonably complete measurements of RNA and protein complements, this view as changed dramatically. The overwhelming majority of transcribed RNA exerts in function, which most likely is of regulatory nature, without ever being translated in protein. Functional RNAs can be identified by their conservation in evolutionary related organism, and often be the preservation of structural features even in the presence of large sequence divergence. The computation and comparison of RNA structures give rise to a variety of challenging computational problems. In my presentation I will give an overview of the state of the art in RNA bioinformatics, with an emphasis on those topics and questions where modern visualization strategies could drastically improve the insights into the data and help the generation of new hypotheses: structure comparison, evolutionary changes in large, complex transcript networks, as well as genome-wide patterns in relation to a wide variety of other genomic features.
Bio: Peter F. Stadler received his Ph.D. in Chemistry from the University of Vienna in 1990 following studies in chemistry, mathematics, physics and astronomy. After a PostDoc at the Max Planck Institute for Biophysical Chemistry in Goettingen he returned to Vienna to work in the area to theoretical biochemistry. Since 1994 he is External Professor at the Santa Fe Institute, a research center focussed on Complex Systems. In 2002 he moved to the University of Leipzig as Full Professor of Bioinformatics. Since 2010 he is External Scientific Member of the Max Planck Society affiliated with the MPI for Mathematics in the Sciences. The general theme of his research is the search for a consistent understanding of biological processes (with an emphasis on (molecular) evolution) at the genotypic, phenotypic, and dynamical level. The techniques range from the analysis of the dynamical systems arising in chemical kinetics and population genetics, to large scale simulations of RNA evolution and the analysis of viral sequence data, to knowledge- based protein potentials, and to algebraic combinatorics applied to the study of fitness landscapes.