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Dr Jason Whyte
Associate Investigator
The University of Melbourne
I like to ask awkard questions, such as "What does your model already know about the value of your planned experiments?"
My PhD research commenced at The University of Adelaide and was completed at the University of Melbourne with submission of my thesis for examination in December 2016. It relates to properties of models employed in describing biomolecular interactions studied with a flow-cell optical biosensor. This has led to the first methods for testing continuous-time linear switching systems for the property of global a priori identifiability. The presence of this property in a model indicates those experiments that may lead to unique parameter estimates, whilst its absence shows those which certainly cannot.
Past positions include:
- Research associate in the School of Mathematical Sciences,The University of Adelaide. The position related to the modelling of water resources. Achievements included the development of novel time series models and methods for discriminating between alternative models producing similar predictions according to one measure of goodness of fit.
- A short term position working on computational aspects of within-host malaria modelling with the Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne.
- Technical Editor of the ANZIAM Journal working under the direction of Professor Charles Pearce, School of Mathematical Sciences, The University of Adelaide.
Research Interests:
biosensors
experimental design
linear switching systems
mathematical biology
Modelling of biological and environmental systems
Parameter estimation
structural identifiability
symbolic algebra
Qualifications:
Ph.D. (School of Mathematics and Statistics, Melbourne)
B.Sc. (Maths & Comp. Sci, Hons, Adelaide)
B.Sc. (Science, Adelaide)
Publications
Book Chapters
Whyte, J. M.
(2021). Branching out into Structural Identifiability Analysis with Maple: Interactive Exploration of Uncontrolled Linear Time-Invariant Structures.
(R.M., C., J. G., & I.S. K., Ed.).Maple in Mathematics Education and Research: 4th Maple Conference, MC 2020, Waterloo, Ontario, Canada, November 2–6, 2020, Revised Selected Papers. 1, doi: 10.1007/978-3-030-81698-8_27
Invited talks, refereed proceedings and other conference outputs
Whyte, J. M.
(2021). Numerical investigation of structural minimality for structures of uncontrolled linear switching systems with Maple.
Maple Conference 2021.
Whyte, J. M.
(2021). Keyword trends for chemicals may lead regulatory response. Could this hint at tomorrow’s (unknown) poisons?.
Early Career & Student Statisticians Conference (ECSSC 2021).
Whyte, J. M.
(2020). On Using ‘Emerging Interest’ in Scientific Literature to Inform Chemical Risk Prioritisation.
(van Griensven, A., Nossent J., & Ames DP., Ed.).Proceedings of the 10th International Environmental Modelling and Software Society Conference.
Whyte, J. M.
(2020). Branching out into structural identifiability analysis with Maple.
Maple Conference 2020.
Whyte, J. M.
(2020). Frustrated mathematical modelling and changeable destinies: Structural identifiability analysis of models to support useful results.
Seminario de Investigación Interdisciplinar para la Innovación en Ciencia y Tecnología (SICTE).
Whyte, J. M.
(2020). On Using ‘Emerging Interest’ in Scientific Literature to Inform Chemical Risk Prioritisation (with updates).
Emerging Contaminants Workshop 2020.
Whyte, J. M.
(2019). An introduction to the testing of model structures for global a priori identifiability (with examples drawn from Plasmodium falciparum malaria modelling).
Influencing Public Health Policy with Data-informed Mathematical Models.
Whyte, J. M.
(2018). Tend to your model or data may pull the wool over your eyes.
Mathematics of Biological Systems Modelling Symposium, April 2018, Melbourne.
Whyte, J. M.
(2018). Anticipating limitations of biological models can help us avoid the frustration of unanswerable questions.
ACEMS ECR retreat.
Whyte, J. M.
(2018). Biological modelling, and rarely asked questions of the 21st century.
BioInfoSummer, Perth, Dec 3-7 2018.
Whyte, J. M.
(2018). Biological modelling, and rarely asked questions of the 21st century.
Australian Bioinformatics and Computational Biology Society 2018 Conference (ABACBS 2018).
Journal Articles
Zaloumis, S. G., Whyte J. M., Tarning J., Krishna S., McCaw J. M., Cao P., et al.
(2021). Development and validation of an in silico decision-tool to guide optimisation of intravenous artesunate dosing regimens for severe falciparum malaria patients.
Antimicrobial Agents and Chemotherapy. 65(6), e02346-20. doi: 10.1128/AAC.02346-20
Whyte, J. M.
(2018). The practical value of an explicit response model in quantitative uses of Biacore™ biosensors.
bioRxiv. doi: 10.1101/294843
Whyte, J. M.
(2018). GLOBAL A PRIORI IDENTIFIABILITY OF MODELS OF FLOW-CELL OPTICAL BIOSENSOR EXPERIMENTS.
Bulletin of the Australian Mathematical Society. 98(02), 350 - 352. doi: 10.1017/S0004972718000357
Publicly available softwares