I'll be speaking on TDA, angiogenesis, and disease diagnostics today at #SIAMLS22 in MS18 at room 336 from 4:30-5:00. meetings.siam.org/sess/dsp_p… Come check it out and say hi!

4/4 ... But, in case study 4, we get great parameter estimation using a modified logistic model w/ spatial correlations from bit.ly/3yoPE1P. But, these types of models are difficult to derive in practice.

2/4 Re:AIC/BIC: In previous work in #BullMathBio (w/ simulated PDE data), we did find situations of overfitting w/ complex learned models. To remedy, we learned 3 models and then used AIC on simulated models for selection (step 3 of pipeline). bit.ly/3jfOcIs

The good part of not being able to sleep at 4 AM is catching @a13xbrowning 's Paper prize winning talk @smb2021! Congratulations and well deserved, Alex! Fantastic talk.

...to partition many model simulations into robust and biologically interpretable groupings based on input parameters! Joint work with Bernadette Stolz, @haharrington, Kevin Flores, and Helen Byrne Pre-print: tinyurl.com/22k4va4h Code: github.com/johnnardini/Angio… 4/4

Unfortunately, this discrete agent-based model is difficult to study in a data-driven manner due to its stochastic and discrete nature. I'll be discussing how topological data analysis methods can overcome these challenges ... 3/4

The Anderson-Chaplain model (tinyurl.com/3y6dj4h9) of tumor-induced angiogenesis is beloved in the Mathbio community because it is simple yet able to capture experimentally-observed blood vessel morphologies 2/4

I'll speaking at @smb2021 today in the CDEV-1 MS session (9:30-11 AM Pacific /12:30-2 PM Eastern/5:30-7 PM BST/ 1:30-2 AM KST) on "Topology discriminates parameter regimes in a model of angiogenesis" @SMBdevBio 1/4

Curious to see what all the buzz is about ...

Sunday granola 😋😋