The pace of data accumulation in glycobiology has lately rapidly increased, largely due to high-throughput technologies. In this increasingly data-rich environment, computer science started to play a central role in handling the data, extracting significant biological information, and probing the missing parts of the 'scenery' by prediction, modelling or simulation. Investigating and comparing glycomes by bioinformatics and structural methods has great practical value and sharply increased in popularity in the past couple of years. In this context, advances have also been made with regard to structural aspects of protein N-glycosylation and consequences for glycoprotein folding. In these areas, however, an approach that integrates glycobiology with protein science is necessary.