Personal profile


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

Sungyoung Shin (Senior postdoc fellow)
Shabnam Khatibi (Postdoc fellow)
Mandy Magias (Research Assistant)
Gaya Constance Cremers (PhD student)
Karina Islas Rios (PhD student)
Milad Ghomlaghi (PhD student)
Simon Judah Rosin (PhD student - joint supervision with Tianhai Tian)
Anthony Hart (Honours student)
Mikhail Dias (Honours student)
Jamin Wu (undergraduate scholarship student)
Past Members
Brennan Chong (Honours student - 1st class)
Annette Phoa (Cancer Council VIC Vacation scholarship student)
Mehul Gajwani (summer scholarship student)
Alice Kim (summer scholarship student)
Other lab webpages (under development)

Projects on offer

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):

  • SDG 3 - Good Health and Well-being
  • SDG 7 - Affordable and Clean Energy

Research area keywords

  • Systems Biology
  • Network biology
  • Cancer Research

Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or