Dr. Benedikt Obermayer
87: Timoféeff-Ressovsky-House (Genomcentrum)
Evolutionary modeling and inference in computational systems biology
As more genomes of various animal species get sequenced, computational biology gains new power to understand biology from an evolutionary perspective. I'm interested in evolutionary inference methods to explore features of regulatory networks and discover new genes. For instance, I used evolutionary correlations in the conservation of microRNA target sites to understand collective functions of post-transcriptional gene regulation. Recently, I became interested in small open reading frames (ORFs). So-called micropeptides encoded by these ORFs have emerged as important regulators of development and physiology, but computational identification is challenging due to their small size. We identified hundreds of novel small ORFs encoding putatively functional peptides from their characteristic conservation signatures. Collaborating with a number of labs at the MDC and elsewhere, we now use these predictions to investigate micropeptide functions in vitro and in vivo.