Projects per year
Personal profile
Biography
Dr Sungyoung Shin received a bachelor’s degree in Electronics (Feb. 2000), a master’s degree (Feb. 2002) in Control Engineering, and a PhD (Aug. 2007) in Systems Biology at University of Ulsan (South Korea), funded by Ministry of Science and Technology (South Korea). After the completion of his PhD, he joined Laboratory for Systems Biology and Bio-Inspired Engineering (SBIE), KAIST (Korea Advanced Institute of Science and Technology) in Daejeon, South Korea. In April 2009, he was promoted to become an assistant research professor. In May 2013, he moved to Ireland and joined Systems Biology Ireland (SBI), University College Dublin as a research scientist (2013-2014) and a Marie Curie Fellow (2014-2015). In October 2015, he joined the Department of Biochemistry and Molecular Biology, School of Biomedical Science at Monash University.
Research interests
Over last three decades, we have seen a paradigm shift from the traditional characterisation of individual molecules - how a single gene functions towards an understanding of interactive pathways and networks - how all genes and gene products of a cell work together. Systems biology leads this new paradigm shift for understanding the functional role of genes, proteins, metabolites and cells through their interactions within a much broader context at networks and systems levels.
The systems biology approaches to cope with the complex nature of cellular systems, covering a broad range of spatial and temporal scale rests on two key features of computational (dynamic) modelling and data integration from different sources, such as genomics, transcriptomics, proteomics.
Mathematical models based on quantitative (high throughput) measurement predict and explain how a cell reacts under different conditions, and the variation of different species in the way they react and respond to these conditions, Through this modelling approach we can get more profound understanding and insight into design principle of biological systems, allowing to create better experimental designs, and eventually to control the dynamic behaviour of a biological system.
Deploying a variety of systems biology approaches to tackle important issues such as cancer, inflammatory and cardiac diseases, my research focuses on the development of accurate and predictive computational models, and analysis of the network structure and regulation of cell signalling, in normal and disease-related contexts. Besides, as a complementary approach to mechanistic computational modelling, my research employs a broad range of artificial intelligence (AI) technologies such as a support vector machine, artificial neural network, and deep learning. Main objectives of my study are
- to create an accurate and predictive model to analyse the network structure and regulation of cell signalling, in normal and disease-related contexts,
- to predict biological network responses to therapeutic interventions (e.g., synergistic drug effect),
- to define the most vulnerable drug targets (‘druggable’) whose activity (behaviour or function) can be effectively modulated by a therapeutic,
- to identify biomarkers that predict the responses of patients to drugs before treatment.
Ultimately, a series of my research hopes to contribute to a better understanding of signalling networks at a systems level in normal and disease states, and enhancement of translational medicine that improve diagnosis, treatment, and prevention of disease.
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):
Network
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Systems-level characterization of scaffold protein signalling networks
1/03/22 → 28/02/25
Project: Research
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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 Access8 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 Access3 Citations (Scopus) -
Feedback, crosstalk and competition: Ingredients for emergent non‐linear behaviour in the pi3k/mtor signalling network
Ghomlaghi, M., Hart, A., Hoang, N., Shin, S. & Nguyen, L. K., 1 Jul 2021, In: International Journal of Molecular Sciences. 22, 13, 14 p., 6944.Research output: Contribution to journal › Review Article › Research › peer-review
Open Access7 Citations (Scopus) -
Signaling Heterogeneity is Defined by Pathway Architecture and Intercellular Variability in Protein Expression
Norris, D., Yang, P., Shin, S-Y., Kearney, A. L., Kim, H. J., Geddes, T., Senior, A. M., Fazakerley, D. J., Nguyen, L. K., James, D. E. & Burchfield, J. G., 19 Feb 2021, In: iScience. 24, 2, 23 p., 102118.Research output: Contribution to journal › Article › Research › peer-review
Open Access5 Citations (Scopus) -
Control of Glucocorticoid Receptor Levels by PTEN Establishes a Failsafe Mechanism for Tumor Suppression
Yip, H. Y. K., Chee, A., Ang, C. S., Shin, S-Y., Ooms, L. M., Mohammadi, Z., Phillips, W. A., Daly, R. J., Cole, T. J., Bronson, R. T., Nguyen, L. K., Tiganis, T., Hobbs, R. M., McLean, C. A., Mitchell, C. A. & Papa, A., 15 Oct 2020, In: Molecular Cell. 80, 2, p. 279-295.e1-e8 25 p.Research output: Contribution to journal › Article › Research › peer-review
9 Citations (Scopus)