#MathOnco Issue 75: single-cell sequencing, neoantigen landscape, hybrid models, optimization and best fits
This week in
Math Oncology
July 25, 2019 ~ Issue 75
From the editor
#MathOnco friends,
Greetings from the SMB conference in Montreal! I have greatly enjoyed meeting many of you face-to-face in the past few days. If you did not have an opportunity to join us this week, catch up on the talks via Twitter.
If you're on the lookout for a postdoctoral position and have an interest in multicellular, agent-based, and open-source systems, scroll down to the jobs section for a new announcement via the Math Cancer lab.
-Jeffrey West
#MathOnco Publications
Hybrid modeling frameworks of tumor development and treatment
Authors: Ibrahim M. Chamseddine, Katarzyna A. Rejniak
Critical behavior of spatial networks as a model of paracrine signaling in tumorigenesis
Authors: Philip Tee, Allan Balmain
Best fitting tumor growth models of the von Bertalanffy-PütterType
Authors: Manfred Kühleitner, Norbert Brunner, Werner-Georg Nowak, Katharina Renner-Martin & Klaus Scheicher
Morphophenotypic classification of tumor organoids as an indicator of drug exposure and penetration potential
Authors: Aleksandra Karolak, Sharan Poonja, Katarzyna A. Rejniak
#MathOnco Preprints
Mathematical modeling with single-cell sequencing data
Authors: Heyrim Cho, Russell C. Rockne
The shared neoantigen landscape of MSI cancers reflects immunoediting during tumor evolution
Authors: Alexej Ballhausen, Moritz Jakob Przybilla, Michael Jendrusch, Saskia Haupt, ..., Axel Benner, Angelika Beate Riemer, Magnus von Knebel Doeberitz, Matthias Kloor
Optimizing Radiation Therapy Treatments by Exploring Tumour Ecosystem Dynamics in – silico
Authors: Stephan Scheidegger and Harold Fellermann
Nucleation of antagonistic organisms and cellular competitions on curved, inflating substrates
Authors: Maxim O. Lavrentovich, David R. Nelson
Description before prediction: evolutionary games in oncology
Artem Kaznatcheev: "Evolutionary games have established themselves for describing theoretical puzzles in oncology. And sometimes even for resolving those theoretical puzzles. But, to a large extent, this process is data-free or data-light. When some sort of data is used, it is often as an illustration. A way to motivate or justify the model. It is often collected besides the model — not through the model. In this way, most work seems to operate on parallel tracks of theory and experiment."
#MathOnco - Book of the month
When Breath Becomes Air
We sometimes find ourselves hiding in the comfort and safety of the details of math models, neglecting to meditate on the real-world implications of the math. This book is for us.
"At the age of thirty-six, on the verge of completing a decade’s worth of training as a neurosurgeon, Paul Kalanithi was diagnosed with stage IV lung cancer. One day he was a doctor treating the dying, and the next he was a patient struggling to live."
Most clicked links of June
Mathematical Modelling of Phenotypic Selection Within Solid Tumours
Numerical optimal control of a size-structured PDE model for metastatic cancer treatment
Learning-accelerated Discovery of Immune-Tumour Interactions
Growth dynamics in naturally progressing chronic lymphocytic leukaemia
Jobs
NEW: Data-driven modeling of breast cancer metastasis - Postdoc (Paul Macklin)
Postdoctoral Research Position in Computational Oncology (Tom Yankeelov)
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