#MathOnco Issue 76: modeling philosophy, mutation order, spatial constraints, blogging, and more
This week in
Math Oncology
August 1, 2019 ~ Issue 76
From the editor
#MathOnco friends,
If you're subscribed to this newsletter, then you'll no doubt be excited to learn that there is now a dedicated blog for all things Mathematical Oncology. This is intended to be a community-led effort, so please do not hesitate to submit a contribution after reading the first post describing the intention behind blog.mathematical-oncology.org.
-Jeffrey West
#MathOnco Publications
Mathematical Models of Cancer: When to Predict Novel Therapies, and When Not to
Authors: Renee Brady, Heiko Enderling
Modeling breast cancer progression to bone: how driver mutation order and metabolism matter
Authors: Gianluca Ascolani and Pietro Liò
A stochastic individual-based model to explore the role of spatial interactions and antigen recognition in the immune response against solid tumours
Authors: F. Macfarlane, M. Chaplain, T. Lorenzi
Spatially constrained tumour growth affects the patterns of clonal selection and neutral drift in cancer genomic data
Authors: Ketevan Chkhaidze, Timon Heide, Benjamin Werner, Marc J. Williams, Weini Huang, Giulio Caravagna, Trevor A. Graham, Andrea Sottoriva
#MathOnco Preprints
Evolutionary Dynamics of CAR T Cell Therapy
Authors: Gregory J. Kimmel, Frederick L. Locke, Philipp M. Altrock
Robust calibration of hierarchical population models for heterogeneous cell populations
Authors: Carolin Loos, Jan Hasenauer
The Mathematical Oncology Blog
"We propose to launch a community blog for mathematical and computational oncology. A space where we can all develop new ideas, share tips and tricks, and announce or discuss the latest work. Blogging is not new, nor is the passion that many mathematical and computational oncologists feel for communicating ideas, algorithms and equations with each other and the public. But this is often solitary and hard work. Hence, we aim to work together as a community to build the reach of mathematical and computational oncology."
Quantifying Tumor Heterogeneity
Elana Fertig: "As Leo Tolstoy says: "Happy families are all alike; every unhappy family is unhappy in its own way." The cells within a tumor follow that paradigm. While normal cells all behave in a limited set of constrained ways, each cancer cell is malignant in its own way."
#MathOnco - Book of the month
Partial Differential Equations
Theory and Completely Solved Problems
T. Hillen, I.E. Leonard and H. van Roessel:
"We, as authors, were quite concerned about the high pricing of textbooks. Hence, for the second edition, we offer our book under a self-publishing license. This allows us to attain professional quality, while being able to set affordable prices. This textbook has been class tested for many years and it is a professionally produced textbook for a third-year PDE course. It offers many learning tools that allow students to make progress and master the material. "
Most clicked links of July
Personalized Therapy Design for Liquid Tumors via Optimal Control Theory
Consecutive seeding and transfer of genetic diversity in metastasis
Jobs
Data-driven modeling of breast cancer metastasis - Postdoc (Paul Macklin)
Postdoctoral Research Position in Computational Oncology (Tom Yankeelov)
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