Data-Driven Modelling in Mathematical Biology.

28th June and 9th July 2021

An introduction to connecting mathematical models with experimental data including: two lectorials, three keynote speakers, and group projects to allow participants to apply the techniques and ideas from lectorials and keynote speakers to suggested problems.

Register

Themes

There will be three key themes aligned with the keynote speakers research interests (subject to change).

Drug Therapy

Adrianne Jenner
Queensland University of Technology

Collective Migration

Douglas Brumley
University of Melbourne

Infectious Diseases

Rebecca Chisholm
LaTrobe University

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Melanoma spheroids with FUCCI cell cycle staining.
Credit Nikolas Haass, University of Queensland Diamantina Institute.

About this symposium

Mathematical biology is a diverse, cross-disciplinary area of research at the interface of applied mathematics, statistics, biophysics and experimental science. Cross-collaboration between experts in these fields is quickly becoming requisite for impactful research.

This online symposium will foster new collaborations and skill development across each of these fields through talks, lectorials in model calibration, and most importantly, data-driven collaborative projects. These elements will bring together experts in deterministic and stochastic modelling, theoretical analysis (for example, travelling wave analysis), experimental science, model calibration, and statistics. The symposium will conclude with participants presenting results from their group projects.


Speed presentations

Participants introduce themselves in short (1 slide, 2 minutes; to be confirmed) presentations, to be prepared ahead of time. These presentations might answer the following questions:

  1. What are you currently researching?
  2. How would you like to incorporate experimental data in your work?

Group projects

Attendees are encouraged to participate in group projects. Each group project will be aligned with one of the three key themes of the workshop. Conference organisers in collaboration with keynote speakers will form suggestions for interesting problems to explore for each group. For example, a group may be directed to a real experimental data set and simple mathematical model that could be used to explore the data set. Then, using the techniques explored in the lectorials, the group will explore how to connect the experimental data to the mathematical model.

Through this participants will gain hands-on experience of connecting models to data. This experience will allow each group to form suggestions for future modelling and experimental design. On the final day each group will present their methodology and findings. Further details, such as suggested problems, will be provided nearer the time.

Conference Program
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Invited Talks

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Adrianne Jenner

Drug Therapy

blog
Douglas Brumley

Collective Migration

blog
Rebecca Chisholm

Infectious Diseases

Lectorials

Two lectorials will provide participants an introduction to common techniques for connecting mathematical models with experimental data.

author

Oliver Maclaren

University of Auckland
Maximum Likelihood Estimation
author

Christopher Drovandi

Queensland University of Technology
Approximate Bayesian Computation

Schedule

This schedule is subject to change. All times are Brisbane/Sydney/Melbourne (AEST).

Day 1 (Monday, 28th June) 8:00am Welcome and opening
8:10am Invited talk 1: Adrianne Jenner
8:50am Invited talk 2: Douglas Brumley
9:30am Lectorial 1 (Maximum likelihood estimation, Oliver Maclaren)
10:15am Break
11:00am Invited talk 3: Rebecca Chisholm
11:40am Lectorial 2 (Approximate Bayesian computation, Chris Drovandi)
12:30pm Break
1:30pm "Speed" presentations
2:30pm Start group projects
Between Collaborate on group projects.
Day 2 (Friday, 9th July) 9:00am Final day welcome and introduction
9:10am Group work and presentation preparation
1:00pm Group presentations
3:00pm Closing remarks

Register

Registration closed on 7th June 2021.

Disclaimer

The Symposium Organisers and Sponsors (MATRIX and AMSI) respect the privacy of individuals and acknowledge that the information you provide on the form is personal information as defined by privacy legislation. The information is being collected for registrations and reporting purpose.

ap.browning (at) qut.edu.au