Prof David Ascher is currently an NHMRC Investigator and Director of the Biotechnology Program at the University of Queensland. He is also Head of Computational Biology and Clinical Informatics at the Baker Institute.
David’s research focus is in modelling biological data to gain insight into fundamental biological processes. One of his primary research interests has been developing tools to unravel the link between genotype and phenotype, using computational and experimental approaches to understand the effects of mutations on protein structure and function. His group has developed a platform of over 40 widely used programs for assessing the molecular consequences of coding variants (>7 million hits/year).
Working with clinical collaborators in Australia, Brazil and UK, these methods have been translated into the clinic to guide the diagnosis, management and treatment of a number of hereditary diseases, rare cancers and drug resistant infections.
David has a B.Biotech from the University of Adelaide, majoring in Biochemistry, Biotechnology and Pharmacology and Toxicology; and a B.Sci(Hon) from the University of Queensland, majoring in Biochemistry, where he worked with Luke Guddat and Ron Duggleby on the structural and functional characterization of enzymes in the branched-chain amino acid biosynthetic pathway. David then went to St Vincent’s Institute of Medical Research to undertake a PhD at the University of Melbourne in Biochemistry. There he worked under the supervision of Michael Parker using computational, biochemical and structural tools to develop small molecules drugs to improve memory.
In 2013 David went to the University of Cambridge to work with Sir Tom Blundell on using fragment based drug development techniques to target protein-protein interactions; and subsequently on the structural characterisation of proteins involved in non-homologous DNA repair. He returned to Cambridge in 2014 to establish a research platform to characterise the molecular effects of mutations on protein structure and function- using this information to gain insight into the link between genetic changes and phenotypes. He was subsequently recruited as a lab head in the Department of Biochemistry and Molecular Biology at the University of Melbourne in 2016, before joining the Baker Institute in 2019 and the University of Queensland in 2021.
He is an Associate Editor of PBMB and Fronteirs in Bioinformatics, and holds honorary positions at Bio21 Institute, Cambridge University, FIOCRUZ, and the Tuscany University Network.
Queensland Alliance for Agriculture and Food Innovation
Availability:
Available for supervision
In my PhD I analysed and modelled biophysical processes (light interception, transpiration and photosynthesis) and their relationships in apple and pear trees during the growing season and at different levels of plant water status. During this time I collaborated in the upgrade of a functional-structural peach model (L-PEACH). Later I focused my research on the effect of carbohydrates on grapevine and berry growth, as well as the effects of light, temperature and VPD on carbon assimilation and transpiration both at leaf and canopy level.
Currently, I am undertaking research on improving management practices in avocado, macadamia and mango. I am focused on studying architecture, vegetative vigour, crop load and light interception using functional-structural plant modelling to understand the interactions between management practices, environmental factors, plant carbon balance and growth.
Dr Moni holds a PhD in Artificial Intelligence & Data Science in 2014 from the University of Cambridge, UK followed by postdoctoral training at the University of New South Wales, University of Sydney Vice-chancellor fellowship, and Senior Data Scientist at the University of Oxford. Dr Moni then joined UQ in 2021. He also worked as an assistant professor and lecturer in two universities (PUST and JKKNIU) from 2007 to 2011. He is an Artificial Intelligence, Computer Vision & Machine learning, Digital Health Data Science, Health Informatics and Bioinformatics researcher developing interpretable and clinical applicable machine learning and deep learning models to increase the performance and transparency of AI-based automated decision-making systems.
His research interests include quantifying and extracting actionable knowledge from data to solve real-world problems and giving humans explainable AI models through feature visualisation and attribution methods. He has applied these techniques to various multi-disciplinary applications such as medical imaging including stroke MRI/fMRI imaging, real-time cancer imaging. He led and managed significant research programs in developing machine-learning, deep-learning and translational data science models, and software tools to aid the diagnosis and prediction of disease outcomes, particularly for hard-to-manage complex and chronic diseases. His research interest also includes developing Data Science, machine learning and deep learning algorithms, models and software tools utilising different types of data, especially medical images, neuroimaging (MRI, fMRI, Ultrasound, X-Ray), EEG, ECG, Bioinformatics, and secondary usage of routinely collected data.
I am currently recruiting graduate students. Check out Available Projects for details. Open to both Domestic and International students.
Dr. Kelvin Tuong is a Senior Research Fellow/Group Leader at the Ian Frazer Centre for Children’s Immunotherapy Research (IFCCIR), Child Health Research Centre. He is interested in single-cell analysis of immune cells and harnessing adaptive immune receptors for understanding immune cell development and function in health and in cancer.
Dr. Tuong was born and raised in Singapore and moved to Brisbane, Australia, after completing national service in Singapore and obtaining a Diploma in Biomedical Laboratory Technology (Ngee Ann Polytechnic).
Dr. Tuong was originally trained as a molecular cell biologist and gradually transitioned into bioinformatics during his post-doctoral training. He has been very prolific for an early career researcher, having published >50 articles since 2013, with nearly a third of them as first/co-first or last author and has a stellar track record of pushing out highly collaborative work in prestigious journals including Nature, Cell, Science, Nature Medicine, Nature Biotechnology J Exp Med etc. He has the rare combination of having excellent laboratory and bioinformatics skill sets which provide him a strong command of both fundamental immunology and computational approaches.
Dr. Tuong completed his undergraduate Bachelor's degree in Biomedical science with Class I Honours, followed by his PhD in macrophage cell biology and endocrinology at UQ (Prof. Jenny Stow lab and Emiritus Prof. George Muscat lab, IMB, UQ). He then went on to a post-doc position with Emiritus Prof. Ian Frazer (co-inventor of the Gardasil cervical cancer vaccine, UQ Frazer Institute, Translational Research Institute) where he worked on HPV immunology, cervical cancer and skin cancer. In his time in the Frazer lab, he developed an interest in bioinformatics analyses as a means to tackle and understanding immunology problems in health and disease. He then moved to the UK and joined Prof. Menna Clatworthy's lab at the University of Cambridge and Dr. Sarah Teichmann's lab at the Wellcome Trust Sanger Institute. He has focused his interests on single-cell analyses of tissue immune cells, including T and B cells and their specific receptors (TCR/BCR). He has developed bespoke bioinformatics software, including one tailored for single-cell B Cell Receptor sequencing analysis, Dandelion, which he used in one of the largest combined single-cell transcriptomic, surface proteomic and TCR/BCR sequencing dataset in the world, published in Nature Medicine, and more recently in Nature Biotechnology where we introduced a TCR-based pseudotime trajectory analysis method.
Dr. Tuong is now leading the Computational Immunology group at the IFCCIR and his lab is focused on investigating how pediatric immunity is perturbed during cancer at the cellular level and how this information can be used for creating novel warning systems for children with cancer. For potential students/post-docs/trainees interested in joining the team, please contact Dr. Tuong at z.tuong@uq.edu.au.