Associate Dean for Undergraduate Education @IUBloomington @IUluddy • multicellular systems & cancer with @PhysiCell#OpenSource • astrophotography

Joined July 2011
3,182 Photos and videos
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We're so honored to receive the 2019 PLoS Computation Biology Research Prize in Public Impact. We wrote PhysiCell to empower modelers to do new and bigger science. I hope this prizes lets us reach and help even more. @CompCancer @rheiland @IUBloomington @IUSICE @ara_anderson
We're delighted to announce the winners of our 2019 @PLOSCompBiol Research Prize! 🏆 Congratulations to Hadizadeh Esfahani et al plos.io/BAI; Dignon et al plos.io/EMS and Ghaffarizadeh et al plos.io/PI Read more here: plos.io/2VZAEDn
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Yep, this is pretty much how I figured the 11 am caviar promo would turn out at @McDonalds
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Paul Macklin retweeted
Waited in a 90-minute line in the rain to get one last Sprinkles Cupcake before all of the stores shut down forever. Corporate America delivering one last shitty moment to ring out a very shitty year. Fuck 2025 and fuck private equity.
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Paul Macklin retweeted
Thrilled to see our project on the cover of this week's @ScienceMagazine. Incredibly fun and rewarding collab with the public, @eliz_aguilar2 @JuncoWren @imillercrews @MathCancer
As the Moon eclipsed the Sun on 8 April 2024, birds took note. Leveraging nature’s own experiment, scientists and the public joined forces to show how different species responded to sudden midafternoon darkness followed by a new “dawn.” Learn more this week in Science: scim.ag/46J1bN5
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Epic indeed, @JoshuaABull !
What's it like round here? What are the people like? What do they do when they are not doing maths? Do they have fun? Films about people who also do maths. @JoshuaABull
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Paul Macklin retweeted
This week in Math Onco 345: Darwinian evolution, digital twins, multiscale modeling, and antifragility Art: @MathCancer & Heber L Rocha 😎💯
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In a serious case of a weirdly small world, I ran into @Seirin_Lab at @OxUniMaths in the visitor office. What a joy!
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They were able to show how cancer-fibroblast interactions can drive malignant transformation (EMT), but in some cases, these interactions can also trap cancer cells to prevent spread. 10/n
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It was a great honor to work with this team. We have accomplished something beautiful together we could never have done on our own. It is an honor to count them as colleagues and friends! 16/n
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And we're beyond grateful for early support by the @JKTGFoundation (and even earlier by @BCRFcure) and @theNCI and @NIH. Without early support for basic sciences, we would never have been in the position to create this work today! 17/17
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Digging deeper Jeanette Johns and Daniel Bergman led work with Elana Fertig and a wide network of collaborators (including Laura Wood, Andy Ewald, Jude Phillips and others) to create a model of pancreatic cancer (PDAC) 7/n
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They were able to use the grammar to entirely encode the complex model (again, no hand-written code!) including complex relationships between ECM density and cell migration that were revealed by experiments at Johns Hopkins. 9/n
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They led innovative work to learn cell identities, positions, and even cell rules directly from spatial transcriptomics (single-cell gene sequencing that preserves cell position), and directly initialized models from individual patients! 8/n
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We worked closely with Laura Heiser, Joe Gray, Lisa Coussens, and Young Hwan Chang at @OHSUKnight to write a model of ~12 simple rules to get immune response to a hypoxic tumor, including eventual immune exhaustion. Zero C . 6/n
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This paper is critical step in that direction, introducing a plain language "grammar" that directly transforms intuitive hypotheses into models in real time, without writing code. Statements like "IL6 increases migration speed in macrophages" map to math & code in real time. 3/n
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We showed a lot of examples using the new grammar, including re-writing prior modeling work with Daniele Gilkes (@GilkesLab @JohnsHopkins) where breast cancer cells respond to low O2 by increasing invasion. This model can be written in minutes without C in our new grammar. 5/n
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Model rules can be written in plain language by experts, literature mining, or data analysis. New rules can augment old rules without breaking them, allowing us to aggregate and refine share knowledge over time! This opens up "virtual labs" to entirely new communities. 4/n
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