#MathOnco Issue 94: genetic instability, resistance and tolerance, cancer risk, immune recruitment, Lotka, EvoFreq
This week in
Math Oncology
Dec. 19, 2019 ~ Issue 94
From the editor
Hello!
Today I've included some links on genetic instability, resistance and tolerance, cancer risk, immune recruitment, and more. Also, the R package for visualizing evolution, EvoFreq, was published this week (which I've written a tutorial on previously!).
For something a bit different today, I've included a 2015 article summarizing the life and work of Alfred J. Lotka.
Please enjoy!
-Jeffrey West
#MathOnco Publications
Genetic instability as a driver for immune surveillance
Authors: Guim Aguadé-Gorgorió & Ricard Solé
EvoFreq: visualization of the Evolutionary Frequencies of sequence and model data
Authors: Chandler D. Gatenbee, Ryan O. Schenck, Rafael R. Bravo & Alexander R. A. Anderson
The evolution of resistance and tolerance as cancer defences
Authors: Frédéric Thomas, Mathieu Giraudeau, Flora Gouzerh, Justine Boutry, ..., Jens Osterkamp, Benjamin Roche, Rodrigo Hamede, Beata Ujvari
Elucidating the correlations between cancer initiation times and lifetime cancer risks
Authors: Hamid Teimouri, Maria P. Kochugaeva & Anatoly B. Kolomeisky
#MathOnco Preprints
From zygote to a multicellular soma: body size affects optimal growth strategies under cancer risk
Authors: E. Yagmur Erten, Hanna Kokko
Eco-evolutionary control of pathogens
Authors: Michael Lässig, Ville Mustonen
Delicate balances in cancer chemotherapy: Modeling immune recruitment and emergence of systemic drug resistance
Authors: Anh Phong Tran, M. Ali Al-Radhawi, Irina Kareva, Junjie Wu, David J. Waxman, Eduardo D. Sontag
A novel network controllability algorithm to target personalized driver genes for discovering combinational drugs of individual cancer patient
Authors: Wei-Feng Guo, Shao-Wu Zhang, Tao Zeng, Luonan Chen
Investigating the Role of Hypoxia-Induced Migration in Glioblastoma Growth Rates
Authors: Lee Curtin, Andrea Hawkins-Daarud, Kristoffer G. van der Zee, Kristin R. Swanson, Markus R. Owen
Alfred J. Lotka and the origins of theoretical population ecology
Sharon Kingsland: "The equations describing the predator–prey interaction eventually became known as the “Lotka–Volterra equations,” which served as the starting point for further work in mathematical population ecology. Charles Elton later explained why this model had such deep impact (7). Ecologists normally thought in terms of entire food chains, which might have five stages, as the means of controlling populations: each species at a higher level was thought to control the species lower down the chain."
#MathOnco - Book of the month
The Art of Theoretical Biology
Franziska Matthäus, Sebastian Matthäus, Sarah Harris, Thomas Hillen: "This beautifully crafted book collects images, which were created during the process of research in all fields of theoretical biology. Data analysis, numerical treatment of a model, or simulation results yield stunning images, which represent pieces of art just by themselves. The approach of the book is to present for each piece of visualization a lucid synopsis of the scientific background as well as an outline of the artistic vision."
Most clicked links of Oct/Nov
Inferring Tumour Proliferative Organisation from Phylogenetic Tree Measures in a Computational Model
Dynamics of tumor growth: chemotherapy and integrative oncology
Key challenges facing data-driven multicellular systems biology
On measuring selection in cancer from subclonal mutation frequencies
Jobs
NEW: Pre-leukemic Dynamics – MSc or PhD Studentship (Morgan Craig)
Quantitative Systems Pharmacology (QSP) Modeler - Cell Therapy (Dean Bottino)
Math/statistical models of stem cell lineage dynamics and cancer genomics - Postdoc (Adam MacLean)
Postdoctoral Research Position in Computational Oncology (Tom Yankeelov)
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