Just as computational approaches for analysing genetic sequence data have revolutionised biological understanding, the expectation is that analyses of biological networks will have similar groundbreaking impacts. However, dealing with network data is nontrivial, since many methods for analysing large networks fall into the category of computationally intractable problems.
We develop methods for extracting new biological knowledge from the wiring patterns of large molecular network data, linking network wiring with biological function and translating the information hidden in the wiring patterns into everyday language. We apply our methods to other domains, including tracking the dynamics of the world trade network and finding new insights into the origins of wealth and economic crises.
More about Dr Natasa Przulj
Natasa is a Reader (Associate Professor) in the Department of Computing, Imperial College London. At Imperial she is also a member of the Institute of Systems and Synthetic Biology, the Centre for Bioinformatics, and the Centre for Integrative Systems Biology (CISBIC). She was an Assistant Professor in the Department of Computer Science at the University of California Irvine from 2005 to 2009. She obtained her PhD in Computer Science from the University of Toronto, Canada, in 2005.
Dr. Przulj is a Fellow of the British Computer Society. In 2014 she was awarded the British Computer Society Roger Needham Award for a distinguished research contribution in computer science by a UK-based researcher within ten years of their PhD. In 2013 she was elected into the Young Academy of Europe. She received a prestigious European Research Council (ERC) Starting Independent Researcher Grant in 2012 for her project entitled "Biological network topology complements genomes as a source of biological information".
She held a prestigious NSF CAREER Award for the project entitled "Tools for analyzing, modelling and comparing protein-protein interaction networks", 2007-2011 at the University of California Irvine. Her research has also been supported by other large governmental and industrial grants including those from GlaxoSmithKline, IBM and Google.