Projects per year
Personal profile
Biography
Dr Lan Nguyen studied Applied Mathematics and Computing at Lincoln University (New Zealand) funded by the New Zealand Study Award. He was soon after introduced to the mysteriously wonderful world of cell biology and became deeply interested in interdisciplinary research that integrates cell biology and mathematical modelling. He went on to complete Ph.D in Computational Systems Biology early 2010, funded by the NZ TEC's Top Doctoral Achiever scheme, under Prof. Don Kulasiri at Lincoln. He then joined Systems Biology Ireland (SBI), a leading systems biology institute in Europe, to carry out postdoc under the mentorship of Prof. Boris Kholodenko and Walter Kolch, world experts in modelling and signal transduction. He became a group leader at SBI in 2014. He joined Monash University in September 2015 as a Senior Research Fellow and Head of the Computational Network Modelling Lab in the Dept. of Biochemistry and Molecular Biology.
Research Interest
Cells in our bodies respond to extracellular cues utilizing not just isolated proteins, but their highly ordered responses result from coordinated actions of networks of proteins. Just like an orchestra symphony is a product of multiple instruments rather than any single one, producing beautiful blended music. This understanding together with the availability of a huge amount of large-scale data brought about by advances in 21st century's measurement technologies, has instigated a new paradigm of biological research termed 'systems biology'. In a nutshell, 'systems biology' aims to obtain a holistic, systems view of biological processes, where the system is more than the sum of its parts. The Nguyen Lab deploys systems biology approaches to tackle key issues in cancer research. As cancer is by nature a systems disease and resistance to anti-cancer drugs is inherently a systems problem, quantitative systems approaches have been and will be instrumental in our quest to understand cancer and conquer drug resistance.
The unifying research theme of the Nguyen Lab focuses on the development an employment of predictive mathematical network models to analyse the network structure and regulation of cell signalling, in normal and cancer-related contexts. The main objectives 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.
Lab members
Shabnam Khatibi (Postdoc fellow)
Mandy Magias (Research Assistant)
Karina Islas Rios (PhD student)
Milad Ghomlaghi (PhD student)
Simon Judah Rosin (PhD student - joint supervision with Tianhai Tian)

http://www.med.monash.edu.au/biochem/staff/lan-nguyen.html
Projects on offer
https://supervisorconnect.med.monash.edu/research-projects?combine=Dr%20Lan%20Nguyen
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Research area keywords
- Systems Biology
- Network biology
- Cancer Research
Network
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Defining the molecular switches that govern discrete cellular fates
Nguyen, L., Schittenhelm, R. & Kriegsheim, A. V.
21/12/21 → 20/12/24
Project: Research
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Exploiting network vulnerabilities to devise effective combination therapies against breast cancer
Nguyen, L., Abud, H., Schittenhelm, R. & Daly, R.
1/10/20 → 31/08/23
Project: Research
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Integrated Multimodal System for Multiplexed Imaging of Signal Transduction
James, D. E., Burchfield, J. G., Francois, M., Jolliffe, K., Waterhouse, A., Hardeman, E. C., Halstead, J. M., Daly, R., Neely, G. G., Nguyen, L., Boecking, T., Rasko, J. E., Jackson, S., Lock, J. & Bertolino, P.
Monash University – Internal University Contribution, Monash University – Internal Faculty Contribution
23/06/21 → 22/06/22
Project: Research
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A Boolean-based machine learning framework identifies predictive biomarkers of HSP90-targeted therapy response in prostate cancer
Shin, S. Y., Centenera, M. M., Hodgson, J. T., Nguyen, E. V., Butler, L. M., Daly, R. J. & Nguyen, L. K., 19 Jan 2023, In: Frontiers in Molecular Biosciences. 10, 16 p., 1094321.Research output: Contribution to journal › Article › Research › peer-review
Open Access -
The pseudokinase NRBP1 activates Rac1/Cdc42 via P-Rex1 to drive oncogenic signalling in triple-negative breast cancer
Yang, X., Cruz, M. I., Nguyen, E. V., Huang, C., Schittenhelm, R. B., Luu, J., Cowley, K. J., Shin, S-Y., Nguyen, L. K., Lim Kam Sian, T. C. C., Clark, K. C., Simpson, K. J., Ma, X. & Daly, R. J., 10 Mar 2023, In: Oncogene. 42, 11, p. 833–847 15 p.Research output: Contribution to journal › Article › Research › peer-review
Open Access -
Relationship Between Dimensionality and Convergence of Optimization Algorithms: A Comparison Between Data-Driven Normalization and Scaling Factor-Based Methods Using PEPSSBI
Degasperi, A., Nguyen, L. K., Fey, D. & Kholodenko, B. N., 2022, Methods in Molecular Biology. Vanhaelen, Q. (ed.). 1st ed. New York NY USA: Humana Press, p. 91-115 25 p. (Methods in Molecular Biology; vol. 2385).Research output: Chapter in Book/Report/Conference proceeding › Chapter (Book) › Other › peer-review
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Akt phosphorylates insulin receptor substrate to limit PI3K-mediated PIP3 synthesis
Kearney, A. L., Norris, D. M., Ghomlaghi, M., Wong, M. K. L., Humphrey, S. J., Carroll, L., Yang, G., Cooke, K. C., Yang, P., Geddes, T. A., Shin, S., Fazakerley, D. J., Nguyen, L. K., James, D. E. & Burchfield, J. G., Jul 2021, In: eLife. 10, 32 p., e66942.Research output: Contribution to journal › Article › Research › peer-review
Open Access11 Citations (Scopus) -
Dynamic modelling of the PI3K/MTOR signalling network uncovers biphasic dependence of mTORC1 activity on the mTORC2 subunit SIN1
Ghomlaghi, M., Yang, G., Shin, S-Y., James, D. E. & Nguyen, L. K., Sep 2021, In: PLoS Computational Biology. 17, 9, 26 p., e1008513.Research output: Contribution to journal › Article › Research › peer-review
Open Access4 Citations (Scopus)