M3s (B. Hatzikirou)
@M3sBiomath
Associate professor in mathematical biology @KhalifaUni ° Group leader @tu_dresden/RT is not endorsement
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Here's a nice "proof without words": The sum of the squares of several positive values can never be bigger than the square of their sum. This picture helps make sense of how ℓ₁ and ℓ₂ norms regularize and sparsify solutions (resp.). [1/n]
Just out in Science (2025)—a landmark study by @Dr_CJackson et al. identifies a previously uncharacterized immune cell population in human glioblastoma (GBM), termed early myeloid-derived suppressor cells (E-MDSCs) (@MichaelLimMD , @BettegowdaMDPHD , @jihk99 , @dpardol1 ). These…
For those interested, some details of the forthcoming book "Mathematical Oncology", Chaplain & Preziosi: 🧵
📢📜 New #mathonco preprint out ! Mathematical models can forecast tumor growth and treatment response, but robust strategies are needed for their validation. We review the state of the art for this task, and outline existing challenges for future work. arxiv.org/abs/2502.19333
Επειδή έχουν ακουστεί ονόματα σταθμών και δημοσιογράφων που καμία σχέση δεν έχουν με την υπόθεση, να ξεκαθαρίσω πως το βίντεο του Greekonomics για την Διαπλοκή έριξαν με ΝΟΜΙΚΕΣ διαδικασίες και απειλές ο ΣΚΑΙ και ο κ. Πορτοσάλτε.
1/🚀 Excited to share RegVelo, our new computational model combining RNA velocity with gene regulatory network (GRN) dynamics to model cellular changes and predict in silico perturbations. Here's how it works and why it matters! 🧵👇 biorxiv.org/content/10.110…
Excited about this collaborative work in @iScience_CP on comparing the Notch signaling models with least microenviroometal uncertainty principle model proposed by @arnabbarua10 @M3sBiomath. Led by @PujarAditi with inputs from @UshasiRoy2 @divyoj & Partha @BE_IISc @Physics_at_IISc
I am very excited that our collaboration of @arnabbarua10 and @mkjolly15 team (Aditi Pujar, @UshasiRoy2, @divyoj and Partha Dey) is finally published. Thread follows /1 cell.com/iscience/fullt…
Thrilled to see our latest research featured in the MathOnco blog! Thanks for the chance to share our work with such a wide audience! For those interested, you can check out the full paper here: doi.org/10.1371/journa…
This week in MathOnco 304: - drug antagonism, - identifiability, - plasticity, - virtual trials, - and more... Art: Simon Syga (@sisyga91) 😎💯
Our new study on understanding tumor heterogeneity with @sisyga91 , @Andreas52436912 ,Harish Jain and Marcus Kellner published in journals.plos.org/ploscompbiol/a…
Tumor heterogeneity is a major obstacle to effective cancer treatment. It is caused by multiple factors, including irreversible mutations and reversible phenotypic changes. But how can we model the interplay between both processes and what's their effect on cancer treatment? 1/
Had a fantastic time at the final conference of my PhD journey in Toledo. Grateful to the organizers of @ecmtb2024 for their excellent preparations and to all the inspiring people I met and the enriching talks I attended. #mathbio #mathematical_biology
Ismaila Mohammad from @KhalifaUni team give his talk at the session „model reduction and identifiability“. @ecmtb2024 #Toledo
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
Excited to share my latest research on predicting glioma recurrence! Using an in-silico model, we found that macrophage density at the tumor edge improves prediction accuracy. Localized biopsies provide vital insights, enhancing post-resection prognosis. #Glioblastoma
The Role of Biopsy Position and Tumor-Associated Macrophages for Predictions on Recurrence of Malignant Gliomas: An In Silico Study biorxiv.org/cgi/content/sh… #bioRxiv
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