Rational vaccine design using computational models

The past few years has seen an abundance in sequence data for viruses such as SARS-CoV-2, HIV and HCV. This information can be exploited for the rational design of vaccines, by building models which capture the patterns in the viral sequences. These patterns can be exploited to find weaknesses in the virus, which can then be used to design effective vaccines.

Representative publications

1. MS Sohail, R. H. Y. Louie , Z Hong, JP Barton, MR McKay. Inferring epistasis from genetic time-series data. Molecular Biology and Evolution 39 (10)
2. MS. Sohail*, R. H. Y. Louie* , J. P. Barton, and M. R. McKay, “MPL resolves genetic linkage in fitness inference from complex evolutionary histories”, Nature Biotechnology. 2021 *Equal contribution
3. A. A. Quadeer, M. R. McKay, J.P. Barton, R.H.Y. Louie , “MPF-BML: a standalone GUI-based package for maximum entropy model inference”, Bioinformatics, 36 (7), pp 2278-2279, April, 2020
4. A. A. Quadeer, R.H.Y. Louie and M. R. McKay, "Identifying immunologically-vulnerable regions of the HCV E2 glycoprotein and broadly neutralizing antibodies that target them”, Nature Communications, 10 (1), pp. 1-11, 2019
5. R. H. Y. Louie , K. J. Kaczorowski, J. P. Barton, A. K. Chakraborty, and M. R. McKay, “The fitness landscape of the human immunodeficiency virus envelope proteins that are the targets of humoral immune responses”, Proceedings of the National Academy of Sciences of the USA (PNAS), 115:E564-E573, Jan 2018.
6. A. A. Quadeer, R.H.Y. Louie , K. Shekhar, A. K. Chakraborty, I. Hsing, and M. R. McKay, “Statistical linkage of mutations in the non-structural proteins of Hepatitis C virus exposes targets for immunogen design,” Journal of Virology, vol. 88, no. 13, pp. 7628-7644, July 2014

More information

Honors and postgraduate opportunities are available. Please send your CV and academic transcript to Raymond Louie.

Developing a machine learning model to predict disease outcome

Accurately predicting disease outcomes can have a significant impact on patient care, leading to early detection, personalized treatment plans, and improved clinical outcomes. Machine learning algorithms provide a powerful tool to achieve this goal by identifying novel biomarkers and drug targets for various diseases. By integrating machine learning algorithms with biological data, you will have the opportunity to push the boundaries of precision medicine and contribute to algorithms that can revolutionize the field. Such biological data includes single-cell datasets, where we have considerable experience.

Representative publications

1. Yanping Yang, R. H. Y. Louie et al, "Chimeric Antigen Receptor T Cell Therapy Targeting Epithelial Cell Adhesion Molecule in Gastric Cancer: Mechanisms of Tumor Resistance", Cancers, 2023.
2. R. H. Y. Louie et al, "CAR+ and CAR− T cells share a differentiation trajectory into an NK-like subset after CD19 CAR T cell infusion in patients with B cell malignancies", Nature Communications, 2023
3. M Gupta, H Balachandran, R. H. Y. Louie , H Li, D Agapiou, E Keoshkerian, et al, “High activation levels maintained in receptor‐binding domain–specific memory B cells in people with severe coronavirus disease” Immunology and Cell Biology 101 (2), 142-155. 2023.
4. C Cai, J Samir, MR Pirozyan, TN Adikari, M Gupta, P Leung, B Hughes, R. H. Y. Louie et al., Identification of human progenitors of exhausted CD8+ T cells associated with elevated IFN-γ response in early phase of viral infection. Nature Communications 13 (1), 7543. 2022.
5. Kenneth P Micklethwaite, Kavitha Gowrishankar, Brian S Gloss, Ziduo Li, Janine A Street, Leili Moezzi, Melanie A Mach, Gaurav Sutrave, Leighton E Clancy, David C Bishop, R. H. Y. Louie , Curtis Cai, Jonathan Foox, Matthew MacKay, Fritz J Sedlazeck, Piers Blombery, Christopher E Mason, Fabio Luciani, David J Gottlieb, Emily Blyth. “Investigation of product-derived lymphoma following infusion of piggyBac-modified CD19 chimeric antigen receptor T cells”, Blood, 2021
6. R. H. Y. Louie and F. Luciani, “Recent advances in single‐cell multimodal analysis to study immune cells”, Immunology and Cell Biology, 2021.

More information

Honors and postgraduate opportunities are available. Please send your CV and academic transcript to Raymond Louie.

Computational methods for fast, lightweight and live nanopore sequencing analysis

Third generation Nanopore sequencing is an emerging technology that has countless applications in fields such as precision medicine, forensics and agriculture. While handheld portable nanopore sequencing devices exist, powerful computers are required to perform subsequent data analysis. This project aims to create improved, highly efficient analysis methods and designs for the future creation of custom computer hardware for portable nanopore analysis. Work involves the design of new algorithms and data structures that maps well to modern computer systems and accelerating those using technologies such as SIMD, GPU, and FPGA.

Representative publications

1. Gamaarachchi, H. , Samarakoon, H., Jenner, S.P., Ferguson, J.M., Amos, T.G., Hammond, J.M., Saadat, H., Smith, M.A., Parameswaran, S. and Deveson, I.W., 2022. Fast nanopore sequencing data analysis with SLOW5. Nature biotechnology, 40(7), pp.1026-1029.
2. Gamaarachchi, H. , Lam, C.W., Jayatilaka, G., Samarakoon, H., Simpson, J.T., Smith, M.A. and Parameswaran, S., 2020. GPU accelerated adaptive banded event alignment for rapid comparative nanopore signal analysis. BMC bioinformatics, 21, pp.1-13.
3. Shih, P.J., Saadat, H., Parameswaran, S. and Gamaarachchi, H. , 2023. Efficient real-time selective genome sequencing on resource-constrained devices. GigaScience, 12, p.giad046.
4. Samarakoon, H., Punchihewa, S., Senanayake, A., Hammond, J.M., Stevanovski, I., Ferguson, J.M., Ragel, R., Gamaarachchi, H.* and Deveson, I.W.*, 2020. Genopo: a nanopore sequencing analysis toolkit for portable Android devices. Communications biology, 3(1), p.538. *joint-senior authors
5. Samarakoon, H., Ferguson, J.M., Jenner, S.P., Amos, T.G., Parameswaran, S., Gamaarachchi, H.* and Deveson, I.W.*, 2023. Flexible and efficient handling of nanopore sequencing signal data with slow5tools. Genome Biology, 24(1), p.69. *joint-senior authors
6. Samarakoon, H., Ferguson, J.M., Gamaarachchi, H.* and Deveson, I.W.*, 2023. Accelerated nanopore basecalling with SLOW5 data format. Bioinformatics, 39(6), p.btad352. *joint-senior authors

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Postgraduate opportunities are available. Candidates are expected to have a strong background in computer engineering with a focus on low-level system programming (must be proficient in C), computer architecture and embedded systems. Previous bioinformatics knowledge is not a must but candidates should be prepared to learn the necessary background material quickly. Enthusiastic and self-motivated candidates who are ready to take up this challenge are requested to contact me via email: hasindu+hdr@unsw.edu.au. In emails you send, make sure to include the ASCII text of the following byte array as the subject (not the byte array, but the ASCII text version). This is to make sure I do not miss emails from genuine and serious candidates amongst hundreds of generic spam emails.

80,0x68,68,32,0b1101111,0x70,112,111,114,116,117,110,105,116,0b1111001,32,105,110,0x20,0x66,97,0x73,116, 32,110,97,110,111,112,0b1101111,114,101,32,97,110,0x61,108,121,115,105,115,32,40,118,48,46,49,46,48,41

Sex differences in disease

Many diseases affect men and women differently. Of individuals suffering from autoimmune disease, approximately 80% are female. Despite decades of study, a critical gap in our understanding underlying these differences still remains. In particular, the cell-types, genes, gene interactions and regulatory networks generating sex differences in the immune system and how these manifest into disease. More broadly, post-viral illnesses such as long-COVID, and ME/CFS, are also female biased, while cancers are generally male-biased.

Representative publications

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More information

Honors and postgraduate opportunities are available. Please send your CV and academic transcript to Sara Ballouz.