Søren Brunak

Name: 
Søren Brunak
Faculty: 
University of Copenhagen, Denmark

Brunak's main research is in Bioinformatics and systems biology. In particular, machine learning based prediction and the general area of integrative systems biology where heterogeneous data from the molecular level are combined with phenotypic data from the healthcare sector. A general aim is to understand disease mechanisms at the level of protein network biology. An additional focus area is human proteome variation and precision medicine, where patient-specific adverse drug reaction profiles and the discrimination between treatment related disease correlations and other comorbidities are investigated. The group engages in non-hypothesis driven research, where massive amounts of data from widely different experimental technologies are combined and analysed with the objective of making discoveries that emerge from the data rather than being the result of specific experiments designed to confirm or disprove given hypotheses. Over the years the Brunak group has also been highly active with the development of novel machine learning based methods and have produced numerous, highly used prediction methods, including SignalP, TargetP, NetGene, NetPhos, NetOglyc, NetNES, distanceP and many others.