Professor and e-Science Faculty Björn Wallner, computational bioinformatician, focusing on protein structure prediction, modeling and dynamics, is deeply involved in developing the Rosetta software suite for modeling macromolecules. He successfully integrated sparse proximity constraints to achieve unprecedented accuracy, enabling molecular dynamics studies of proteins without known structure. Together with Prof. Sunnerhagen, he has used computational combined with experimental techniques to study mutation-dependent conformational ensembles in the P. Aeruginosa gene regulator MexR, responsible for antibiotic resistance. By combining explicit modeling of atomic interactions with ambiguous distance constraints they have for the first time described the interaction between the disorded Myc protein to Pin1 at the molecular level. In parallel he developed a predictor of local coordinate error of protein structure models that was ranked no 1 in the community-wide benchmark CASP11 in Dec 2014. The local error estimates have been incorporated into the Phaser software for molecular replacement making it possible to now solve the crystallographic phase problem for more targets using less accurate models. He has predicted protein-protein interactions combining structural comparison and modeling with sequence data and AI to pinpoint evolutionary events responsible for interactions. Recent publications in Bioinformatics, Structure and Nature Structural Biology.