Thanks to modern assay techniques, biology is transforming into a “data-rich” science. With high-throughput sequencing, mass spectrometry, automated perturbation screens and other “big data” assay technologies, we can now get at the same time a “bird's eye” overview as well as plenty of detail on a set of biological samples. The vast amount of raw data produced this way is, however, of little use without powerful bioinformatics and biostatistics methods to process, analyse, and interpret them.

The new bioinformatics group that I am setting up ZMBH focuses on developing the computational tools that biologists need to find the needles of biological insights in the haystacks of high-throughput assay data.

We are working on methods to analyse high-throughput sequencing data, to visually and interactively explore big interlinked data sets, e.g. from omics studies, and on the use of transcriptomcis and proteomics data in functional genomics and systems medicine.