Jana Wolf and her team are one of the few research labs at the Max Delbrück Center for Molecular Medicine (MDC) that only do theoretical work. “We actually sit at our computers all day and perform calculations,” she says. Wolf’s goal is to create increasingly precise mathematical models that help better understand and predict the processes that occur in individual cells and in the whole organism.
“Many biological processes are difficult to investigate and understand using purely experimental methods,” Wolf says. “Our models support the research of our colleagues working in labs – by reproducing their findings or by using the models developed from these findings to gain new insights." So the scientist collaborates extensively with experimental research teams at both the MDC and Charité – Universitätsmedizin Berlin. “We are always the theoretical partner in joint projects,” she says.
More expertise in data analysis
On June 15, 2020, Wolf, who heads a research group at the MDC since 2008, will also begin an academic appointment at the Institute of Mathematics and Computer Science of Freie Universität (FU) Berlin. Her new post is an S-professorship with limited teaching obligations, and it carries the title of Professor of Computer Modeling of Biological Networks. She will have a teaching load of two hours per week – though she will initially be holding all of her lectures online due to the coronavirus pandemic.
“I am excited about my future position at the FU, in particular the opportunity to exchange ideas and discuss research with the mathematicians and computer scientists working there,” says the MDC scientist, who studied theoretical biophysics and received her PhD from Humboldt-Universität zu Berlin and then worked in pharmaceutical research at GlaxoSmithKline in Great Britain. “Our specialization at the MDC is mathematical modeling and now I will be able to draw on the diverse knowledge and experience of my new colleagues at the FU, especially in the area of data analysis. For different problems we can learn a lot from the mathematical and computer science approaches in other disciplines. This includes data analyses driven by machine learning, which is also important in climate or transport research, for example."
A smart substitute for animal testing
Her colleagues at the MDC generate large amounts of data, for example about the genes active in a cell or the proteins produced there. “If we use and process these data properly, then we can develop increasingly better models,” Wolf says. “We can do things such as simulate perturbations in certain biological processes for which there are no experimental tools, or study the influence of several perturbing factors simultaneously, which would probably be too time consuming experimentally.” Wolf hopes that the models – which are also used by the pharmaceutical industry to develop new drugs – will make it possible to replace animal testing altogether in some cases.
Predictive models for medical therapies
It might sound theoretical at first, but it could change the future of medicine in practical ways: “If the molecular causes of a type of cancer are already understood, we can use sophisticated computer models to predict whether a particular cancer therapy – or a combination of various treatment approaches – will, in all likelihood, work,” Wolf explains, adding that such models have not yet been fully established as an intelligent tool for doctors. “But that,” Wolf says, “is precisely our goal.” The new professorship could help make this goal a reality.
Text: Anke Brodmerkel