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Featured Researcher: Dr Lan Nguyen

My Research

Dr Lan NguyenPredictive Network Modelling at Systems Biology Ireland (SBI): The overwhelming complexity of biochemical networks requires quantitative frameworks for efficient analysis of their behaviours. The unifying theme of my group research focuses on the development an employment of predictive mathematical network models to analyse the network structure and regulation of cell signalling, particularly in cancer-related contexts. The main aims are to develop accurate and predictive models using multi-disciplinary tools from experimental biology and mathematical, computational sciences to: (i) analyse the specificity of signalling and adaptation processes, thereby understanding cell-fate decision making mechanisms, (ii) predict network responses to perturbations (such as drugs) and (iii) define the most sensitive points for therapeutic interference (targets identification). The ultimate goal of these lines of research is to obtain better network-level understanding of signalling networks in normal and disease states, based on which novel therapeutic strategies can be derived.


Research Fellow and Junior Group Leader with Prof. Boris KholodenkoProf. Walter Kolch


Christchurch, New Zealand and Thanh Hoa, Vietnam


I studied Applied Mathematics and Computer Science at undergraduate at Lincoln University in Christchurch, New Zealand under the pretigious New Zealand Study Award. Soon after, I was introduced to the mysteriously wonderful world of cell biology and became deeply interested in interdisciplinary research that integrates cell biology and mathematical modelling. I went on to complete my Ph.D degree in Computational Systems Biology in late 2009 under the supervision of Prof. Don Kulasiri at Lincoln. My doctoral research explored the intricate connection between cellular systems behaviour and feedback regulation, focusing on systems governed by multiple negative feedback loops. Another aspect of my thesis looked at effects of molecular noise on the dynamics of biochemical networks. This work is fully funded by the highly competitive New Zealand Top Doctoral Achiever Scholar program.

Career Path

In early 2010, I joined Systems Biology Ireland (SBI) as a postdoctoral research fellow and work under the mentorship of Prof. Boris Kholodenko and Prof. Walter Kolch, who are world leaders in mathematical modelling and signal transduction research. I am currently a Research Fellow and Modelling Group leader at SBI. Among the projects involved, I took an integrated approach combining mathematical modelling and experimental validation to show how competitive protein interactions and phosphorylation effects create functional switches that influence cell fate decisions in the MST2-Raf-1 crosstalk network. This work, where I led the modelling effort and was recently published in Nature Cell Biology, represents an important conceptual advance in our understanding of protein-protein interaction networks and demonstrated the power of an integrated approach to gain functional network-level insight into biological systems. 

In addition, my work in collaboration with the Nobel Laureate Prof. Ciechanover, who discovered the ubiquitin-proteasome system, was published in the leading computational journal PLOS Computational Biology. I also led a project where we constructed the first comprehensive data-driven dynamic model of the hypoxia-induced HIF signalling network, published in the Journal of Cell Science. In 2013-2014, I was awarded a UCD Seed Funding Career Development Award and co-awarded a 3-year Project Grant by the Breast Cancer Campaign UK.
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1. Romano, D., Nguyen, L.K.*, Matallanas, D., Halasz, M., Doherty, C., Kholodenko, B.N., Kolch, W. (2014) Protein interaction switches coordinate oncogenic and apoptotic signaling. Nature Cell Biology doi: 10.1038/ncb2986. *Lead modelling author.

2. Tai Kiuchi#, Elena Ortiz-Zapater#, James Monypenny#, Daniel R. Matthews, Nguyen, L.K.*,, Jody Barbeau, Oana Coban, Katherine Lawler, Brian Burford, Daniel Rolfe, Emanuele de Rinaldis, Dimitra Dafou, Michael A. Simpson, Natalie Woodman, Sarah Pinder, Cheryl E. Gillett, Viviane Devauges, Simon P. Poland, Gilbert Fruhwirth, Pierfrancesco Marra, Ykelien L. Boersma, Andreas Plückthun, William J Gullick, Yosef Yarden, George Santis, Martyn Winn, Boris N. Kholodenko, Marisa Martin-Fernandez, Peter Parker, Andrew Tutt, Simon M. Ameer-Beg, Tony Ng (2014) Competition for the recruitment of the E3 ligase Cbl, in complex with Grb2, within a novel EGFR-ErbB4 CYT2 heterodimer. Science Signalling (in press). *Lead modelling author.

3. Nguyen, L.K.*, Dobrzynski, M., Fey, D., Kholodenko, B.N.* (2014) Ubiquitin chain organization determines the dynamics of protein activation and degradation. Frontier in Systems Biology, special topic: “Organisation, Dynamics and Life” – doi: 10.3389/fphys.2014.00004. eCollection 2014. *Corresponding authors.

4. Nguyen, L.K., Cavadas, M.A.S., Scholz, C.C., Fitzpatrick, S.F., Bruning, U., Cummins, E.P., Tambuwala, M.T., Manresa, M.C., Kholodenko, B.N., Taylor, C.T., & Cheong, A. (2013) A dynamic model of the hypoxia-inducible factor (HIF) network. Journal of Cell Science. doi: 10.1242/jcs.119974. Epub 2013 Feb 6. (Most read paper of JCS, February 2013).

5. Nguyen, L.K., Muñoz-García, J., Maccario, H., Ciechanover, A., Kolch W., & Kholodenko, B.K. (2011) Switches, excitable responses and oscillations in the Ring1B/Bmi1 ubiquitination system. PLoS Computational Biology, 7(12): p. e1002317. (Highlighted in the Conway Research Focus.)

Why choose UCD Conway?

Systems Biology Ireland, based within the UCD Conway Institute, provides a highly stimulating environment for systems biology research. Led by experienced researchers and world leaders in the systems biology field, SBI has been judged by a reputed international advisory board as one of the top systems biology institutes in Europe. SBI’s most valuable asset is its unique interdisciplinary environment where modelling and experimentation are integrated under one roof, and dry and wet scientists work side by side engagingly. Such an environment promotes a greater understanding between these two intertwined disciplines and greatly increases productivity and the quality of research undertaken. 

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