Senior scientist @OCBE_UniOslo, mathematician working on personalized cancer medicine using mechanistic modeling, machine leaning or combinations of both.
If you are interested in immune cells in tumors and their impact on clinical outcomes, our latest work might interest you: biorxiv.org/content/10.1101/…. We pose a simple question: how is the abundance of different cell types associated with treatment response and relapse? 1/n
Leah Edelstein-Keshet (University of British Columbia), Modeling & simulating single cell motility optogenetic experiments birs.ca/events/2024/5-day-wo…
Congratulations to @MyelomaOslo on your public disclosure, “Relapse prediction in multiple myeloma patients treated with isatuximab, carfilzomib, and dexamethasone.” We’re proud to facilitate your access to data #ClinicalResearchdoi.org/10.1101/2024.05.02.2…
Excited to share the fruits of a new collaboration with @AguadeGuim and @ricard_sole on: Modeling tumors as complex ecosystems. This perspective is open access with almost 230 references - out now in @iScience_CPcell.com/iscience/fulltext/S…
Oxford Mathematician and Fellow of @StJohnsOx Philip Maini has been awarded the Sylvester Medal by the @royalsociety for his contributions to mathematical biology.
Pretty good teacher too.
maths.ox.ac.uk/node/68841
Photo: Robert Taylor/St John's
This paper has my vote for Most Interesting & Provocative new ideas in "philosophy of modeling" in the last several years:
frontiersin.org/journals/imm…
My summary: 🧵🧵🧵
30 Essays to Make You Love Biology
Day 1. "I should have loved biology" by James Somers.
"It was only in college, when I read Douglas Hofstadter’s Gödel, Escher, Bach, that I came to understand cells as recursively self-modifying programs."
Great first day at #ECMTB24 including interesting talks on integrating mechanistic models and machine learning in mathematical oncology by @guillelorenzogz and @SBruningk.
Attended to the first session „mechanistic learning in mathematical oncology“ organised by @AlvaroKohn.
Babis @M3sBiomath gave his talk on making clinical predictions without understanding everything.
@ecmtb2024#Toledo#math_onco
Dear ECMTB2024 participants,
The 13th Edition of the European Conference on Mathematical and Theoretical Biology ecmtb2024.org/ is just around the corner so, before arriving in Toledo, we would like to give you some indications.
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Read the article: Computational model predicts patient outcomes in Luminal B breast cancer treated with endocrine therapy and CDK4/6 inhibition.
bit.ly/3Y9UEXR
Thanks for highlighting our recent @CCR_AACR paper predicting patient outcomes in breast cancer treated with endocrine therapy and CDK4/6 inhibition. Also really looking forward to read the ctDNA paper of #JasmineFoo et al. And congratulations on the 300 #MathOnco edition!
Thanks for highlighting our recent @CCR_AACR paper predicting patient outcomes in breast cancer treated with endocrine therapy and CDK4/6 inhibition. Also really looking forward to read the ctDNA paper of #JasmineFoo et al. And congratulations on the 300 #MathOnco edition!
This week in #MathOnco 300!
ecological interactions, predictive modeling, CT DNA kinetics, and more...
Art: Artist: Mark Chaplain (@mcapellanus), Nikos Sfakianakis, Dimitris Katsaounis, Nicholas Harbour, Thomas Williams
Signup: mathematical-oncology.org/ne…
Is our #mathonco modeling clinically relevant? Check our brand new paper @CCR_AACR describing a mathematical model that predicts outcomes in breast cancer patients treated with endocrine therapy and cdk4/6 inhibitors.
aacrjournals.org/clincancerr…
Could we use deep learning to personalize cancer treatment schedules? We explore this in castrate-resistant prostate cancer, in a new paper out in Cancer Research @CR_AACR: doi.org/10.1158/0008-5472.CA…
A tweetorial (or should I now say an eXposition?) [1/11]