Conference on inference methods for mathematical biology

[ben18785]

Dear all,

We would like to invite abstract submissions for presentations & posters for a conference on the intersection of statistical inference and mathematical biology as highlighted below. The conference will consist of a two day meeting held in the Mathematical Institute at the University of Oxford on 23rd-24th May 2022. The conference is partially funded by the London Mathematical Society and the Heilbronn Institute.

We have travel, accommodation and subsistence grants for UK-based early career researchers available. We also have funds available to cover caring costs as a result of attending the conference. If you wish to apply for these funds please indicate so in the form.

Conference title: “Inference for expensive systems in mathematical biology: is it a solved problem or do we need new methods?”

The purpose of this meeting is to bring together mathematical biologists and statisticians to share ideas about best practices for inference across a range of application areas in mathematical biology. Crucially, it will facilitate a dialogue between these two communities which speak largely different mathematical languages. The conference will focus on inference for computationally “expensive” systems in mathematical biology, such as systems of coupled, highly nonlinear ordinary and partial differential equations. Key outcomes of the conference will be to identify those application areas most in need of new inference methods and to expose mathematical biologists to recently developed statistical approaches.

We invite abstracts on work either relating to statistical methods development (so long as those methods are applicable to biological systems) or on the application of statistical methods to solve biological problems. We are especially interested in presentations on biological problems where an inference solution has yet to be found (i.e. unsolved inference problems).

The conference organising committee is committed to ensuring fair participation of individuals across all career stages, genders, races and ethnicities, ages, geographic locations, and universities. Please submit your application here: https://forms.gle/c2G3fXKxM51HEXWb6. The deadline for applications is the 7th February 2022.

Kind regards,

Conference organising committee

[ben18785]

Just a reminder to submit your abstract for the mathematical biology & inference conference happening at the University of Oxford on 23rd-24th May 2022.

The deadline for abstract submission is the 7th February.

An update on invited speakers:

• Prof. Ruth Baker, University of Oxford
• Dr. Marina Riabiz, King’s College London
• Ms. Solveig van der Vegt, University of Oxford
• Prof. Heikke Haario, Lappeenranta-Lahti University of Technology
• Dr. Remi Bardenet, University of Lille
• Prof. George Deligiannidis, University of Oxford

[ben18785]

Dear all,

We would like to invite online attendees to the above conference taking place on the 23rd / 24th May 2022. Online tickets cost £20 for two days and can be purchased here: https://fixr.co/event/inference-for-expensive-systems-in-mathematical-bi-tickets-517620015

The talks include the following, which will be livestreamed from Oxford. Online participants will be able to ask the presenters questions through a messenger service.

– Measuring the accuracy of likelihood-free inference, Aden Forrow, University of Oxford
– Non-stationary noise analysis of whole-cell currents from hERG expression systems, Alejandra D Herrera Reyes, University of Nottingham
– Estimating transmission and prevalence from sequence, occurrence, (and possibly serological) data, Alexander Zarebski, University of Oxford
– Some results on MCMC algorithms for intractable likelihoods, George Deligiannidis, University of Oxford
– Statistical calibration of pattern formation models, Heikki Haario, Lappeenranta University of Technology
– Nonreversible MCMC for latent phylogenetic trees, Jere Koskela, University of Warwick
– Quantifying the relative information in noisy epidemic time series, Kris Parag, University of Bristol
– Kernel Stein discrepancy minimization for MCMC thinning in cardiac electrophysiology, Marina Riabiz, King’s College London
– Four ways to fit an ion channel model, Michael Clerx, University of Nottingham
– History Matching – an alternative way of inference for biological systems, Peter Challenor, University of Exeter
– Monte Carlo methods based on repulsive point processes for generic expensive models, Rémi Bardenet, Ecole Centrale de Lille
– Improved Bayesian inference for ODEs using adjoint methods for gradient-based sampling and adaptive step size selection, Richard Creswell, University of Oxford
– Efficient Bayesian inference for mechanistic modelling with high-throughput data, Ruth Baker, University of Oxford
– Practical parameter identifiability applied to a model of autoimmune myocarditis, Solveig van der Vegt, University of Oxford
– Parameter inference with topological approximate bayesian computation, Tom Thorne, University of Surrey

Note that the conference will also be taking place in person, and the above tickets do not allow in-person attendance. Best, Conference organising committee

[Author]

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