Prof. Natasa Przulj is an elected member of Academia Europaea--The Academy of Europe, The Serbian Royal Academy, and a Fellow of the British Computer Society. She is an ICREA Research Professor at Barcelona Supercomputing Center as of January 1st, 2019. 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. She received two prestigious European Research Council (ERC) grants, ERC Consolidator (2018-23) and ERC Starting (2012-17). She held a prestigious NSF CAREER Award. Her research has also been supported by other large governmental and industrial grants. She was previously a Full Professor (2016-2019) at UCL, Associate Professor (2012-2016) and Assistant Professor (2009-2012) at Imperial College London and an Assistant Prof. at Univ. of California-Irvine (2005-2009). She obtained a PhD in Computer Science from Univ. of Toronto in 2005.
- Molecular and clinical data integration for precision medicine: patient stratification, biomarker discovery, drug re-purposing, drug discovery, disease re-classification
- Data analytics, modeling, fusion, dynamics, applied to clinical, molecular and biological data
- Algorithms for uncovering molecular mechanisms of disease from systems-level “omics” data
- Molecular networks: interactome evolution, dynamics, alignment, function prediction
- Large-scale economic data analysis, fusion and modeling the dynamics of economic systems
- Computational graph theory, algorithms, models
– Malod-Dognin N, Petschnigg J, Windels SFL, Povh J, Hemingway H, Ketteler R & Pržulj N 2019 ‘Towards a data-integrated cell‘. Nat Commun 10, 805.
– Malod-Dognin N, Windels S & Pržulj N2019, ‘Machine Learning for Data Integration in Cancer Precision Medicine: Matrix Factorization Approaches‘, in Analyzing Network Data in Biology and Medicine: An interdisciplinary textbook for biological, medical and computational scientists, Cambridge University Press.
– Pržulj N (ed) 2019, Analyzing Network Data in Biology and Medicine: An Interdisciplinary Textbook for Biological, Medical and Computational Scientists, Cambridge University Press
– Malod-Dognin N & Pržulj N 2019, ‘Functional geometry of protein interactomes‘, Bioinformatics, Volume 35, Issue 19, 1 October 2019, Pages 3727–3734,
– Leal L, Kosir R & Pržulj N, ‘From Genetic Data to Medicine: from DNA samples to disease risk prediction in personalised genetic tests‘, in Analyzing Network Data in Biology and Medicine: An interdisciplinary textbook for biological, medical and computational scientists. Cambridge University Press .
– Windels SFL, Malod-Dognin N & Pržulj N 2019, ‘Graphlet Laplacians for topology-function and topology-disease relationships‘, Bioinformatics, 35, 24, 5226 – 5234.
Selected research activities
Grant: ERC CoG · 01/Apr/2018 – 01/Apr/2023 · Horizon 2020 · ‘Integrated Connectedness for a New Representation of Biology (ICON-BIO)’ · Role: Principal Investigator/Director · Total amount: 2.000.000€