Andrea Degasperi
M.Sc., Ph.D.
Research Associate, University of Cambridge, UK
Mutagenesis in Medicine group
Early Cancer Institute, Hutchison Research Centre, Cambridge, UK
Member of St Edmund's College and EACR

Quick Links: Publications | Software

email ad923 [at) cam [dot) ac [dot) uk
office Early Cancer Institute, University of Cambridge, Hutchison Research Centre, Cambridge Biomedical Campus, Cambridge, UK CB2 0XZ
other office Academic Laboratory of Medical Genetics, Lv 6 Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, UK, CB2 0QQ

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My main interests are both theoretical and applicative aspects of modelling and analysis of complex systems. I like to address problems that are at the boundary across disciplines, where the improvement in terms of analysis of a system or data is driven by field specific questions. This led me to work in a multidisciplinary environment, collaborating with experts from biology, chemistry, medicine, physics and engineering. I spent more than 5 years with Systems Biology Ireland (UCD, Dublin, Ireland) as a postdoc, of which one as a visiting scientist at AstraZeneca (Cambridge, UK). I have worked on signalling pathways in cancer, parameter estimation for systems biology models and on predicting drug effects in high throughput screening using machine learning. In 2017 I moved to the group of Serena Nik-Zainal, initially at the Wellcome Sanger Institute and then at the University of Cambridge, and currently work on mutational signatures in cancer and their application for personalised medicine.


2017-present Research Associate at the University of Cambridge (Cambridge, UK).
2017 Post Doctoral Fellow at Wellcome Sanger Institute (Cambridge, UK).
2016-2017 Post Doctoral SFI Industry Fellow at Systems Biology Ireland, University College Dublin (Ireland) and Visiting Scientist at AstraZeneca (Cambridge, UK).
2011-2015 Post Doctoral Researcher at Systems Biology Ireland, University College Dublin (Ireland).
2007-2011 Ph.D. at the School of Computing Science of the University of Glasgow (UK).
2005-2007 European Masters in Informatics (EuMI) at the University of Edinburgh (UK) and University of Trento (Italy).
2002-2005 Bachelor Degree in Informatics at the University of Trento (Italy).

Attended/Planning to Attend Conferences and Workshops

- EACR Cancer Genomics 2022 (website). July 5th - 7th 2022, Oxford, UK.

- EACR2021 Virtual Congress (website). June 9th - 12th 2021, Online Event.
- EACR2020 Virtual Congress (website). June 18th - 19th 2020, Online Event.
- EACR Cancer Genomics 2019 (website). June 23rd - 26th 2019, Cambridge, UK.
- 25th Biennial Congress of the European Association for Cancer Research (EACR25). June 30th - July 3nd 2018, Amsterdam, Netherlands.
- Cambridge New Therapeutics Forum (website). November 16th 2017, Cambridge, UK.


Highlight Publications:

- A. Degasperi, X. Zou, T. D. Amarante, A. Martinez-Martinez, G. C. C. Koh, J. M. L. Dias, L. Heskin, L. Chmelova, G. Rinaldi, V. Y. W. Wang, A. S. Nanda, A. Bernstein, S. E. Momen, J. Young, D. Perez-Gil, Y. Memari, C. Badja, S. Shooter, J. Czarnecki, M. A. Brown, H. R. Davies, Genomics England Research Consortium, S. Nik-Zainal. Substitution mutational signatures in whole-genome-sequenced cancers in the UK population. Science, doi:10.1126/science.abl9283, 2022.
- G. Koh, A. Degasperi, X. Zou, S. Momen, S. Nik-Zainal. Mutational signatures: emerging concepts, caveats and clinical applications. Nature reviews. Cancer., 2021.
- A. Degasperi, T. D. Amarante, J. Czarnecki, S. Shooter, X. Zou, D. Glodzik, S. Morganella, A. S. Nanda, C. Badja, G. Koh, S. E. Momen, I. Georgakopoulos-Soares, J. M. L. Dias, J. Young, Y. Memari, H. Davies, S. Nik-Zainal. A practical framework and online tool for mutational signature analyses show intertissue variation and driver dependencies, Nature Cancer,, 2020.
- F. Maura, A. Degasperi, F. Nadeu, D. Leongamornlert, H. Davies, L. Moore, R. Royo, B. Ziccheddu, X. S. Puente, H. Avet-Loiseau, P. J. Campbell, S. Nik-Zainal, E. Campo, N. Munshi, N. Bolli. A practical guide for mutational signature analysis in hematological malignancies. Nat Commun., doi: 10.1038/s41467-019-11037-8, 2019.
- A. Degasperi, D. Fey, B. N. Kholodenko. Performance of objective functions and optimisation procedures for parameter estimation in system biology models. npj Systems Biology and Applications, doi:10.1038/s41540-017-0023-2, 2017.
- C. Bendtsen, A. Degasperi, E. Ahlberg, L. Carlsson. Improving Machine Learning in Early Drug Discovery. Annals of Mathematics and Artificial Intelligence, doi:10.1007/s10472-017-9541-2, 2017.
- L. K. Nguyen, A. Degasperi, P. Cotter, B. N. Kholodenko. DYVIPAC: an integrated analysis and visualisation framework to probe multi-dimensional biological networks. Scientific Reports, 5, Article number: 12569. doi:10.1038/srep12569, 2015.
- A. Degasperi, M. R. Birtwistle, N. Volinsky, J. Rauch, W. Kolch, B. N. Kholodenko. Evaluating Strategies to Normalise Biological Replicates of Western Blot Data. PLoS ONE, 9(1): e87293. doi:10.1371/journal.pone.0087293, 2014.
- A. Degasperi and M. Calder. A Process Algebra Framework for Multi-Scale Modelling of Biological Systems. Theoretical Computer Science, Volume 488, pages 15-45, Elsevier, 2013.

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- (R): R package for mutational signature analysis. It includes algorithms for mutational signature extraction and fit, along with HRDetect and many other utility functions.
- SBC/PEPSSBI (Java/C++): Systems Biology Compiler (SBC) or PEPSSBI (Parameter Estimation Pipeline for Systems and Synthetic Biology) is a computer program for the automation of the parameter estimation work flow. It includes automated relative data normalisation, automated data-driven normalisation of the simulations and generation of code for the deployment on a computer cluster with Portable Batch System.
- SBML2SBC (Java): File converter from SBML to the Systems Biology Compiler script language.
- DYVIPAC Python (Python): DYVIPAC is a software program for Systems and Synthetic Biology for relating systems parameters with systems dynamics through visualisation. DYVIPAC uses SBML models as input and explores the model parameter space. It then computes the stability analysis for each parameter set, thus identifying parameter sets for which the given model is capable of, for example, producing stable oscillations or multistability.
- motifGenerator (Java): A signalling pathway motif generator. Combines signalling pathway motifs in an automated and combinatorial way. Part of a pipeline for the design of synthetic signalling pathways. The aim of this software is to explore signalling pathway motifs that can then be tested for desired properties such as bistability and oscillations.
- Process Algebra with Hooks Simulator (Ocaml): monte carlo simulator that uses process algebra with hooks as input, developed for my Ph.D. thesis.

Funding, Scholarships, Awards

- 2017-2020 Cancer Research UK (CRUK) Pioneer Award, awarded to Serena Nik-Zainal.
- 2016-2017 Science Foundation Ireland Industry Fellowship No. 15/IFA/2925, awarded to Andrea Degasperi.
- 2014-2015 European Union Seventh Framework Programme (FP7/2007-2013) grant agreement no 613879 (SynSignal).
- 2011-2013 Science Foundation Ireland Grant No. 06/CE/B1129 (Systems Biology Ireland core grant).
- 2007-2011 Lord Kelvin / Adam Smith Scholarship Ph.D. Scholarship, University of Glasgow.
- 2006-2007 Scholarship for the European Master in Informatics (EuMI) awarded by the University of Trento (Italy).