#MathOnco Issue 50: immune-oncology, tumor niches, dose schedules, density-dependence, evolution models
This week in
Mathematical Oncology
Jan. 17, 2019 ~ Issue 50
From the editor
Hello #MathOnco friends,
As you know, every week I post 3 or 4 preprints. This method of accelerating of science has exploded in popularity over the past several years! You may want to browse this preprint which collected and analyzed data on all 37,648 preprints that were uploaded to bioRxiv in its first five years. The authors note that preprints on bioRxiv are being read more than ever before (1.1 million downloads in October 2018 alone).
Mixed among these math onco articles below, I've also included a couple publications on evolution models (on curved surfaces and density-dependent selection). While these aren't technically oncological models, they may prove inspiring for your model building this week as both are models of cancer-related phenomena.
-Jeffrey West
#MathOnco Publications
Patterns of Tumor Progression Predict Small and Tissue-Specific Tumor-Originating Niches
Authors: Thomas Buder, Andreas Deutsch, Barbara Klink, Anja Voss-Böhme
Modeling hepatitis C virus protein and p53 interactions in hepatocytes: Implications for carcinogenesis
Authors: Maria I. Poole, Inmaculada Sorribes, Harsh Vardhan Jain
Evolution of populations expanding on curved surfaces
Authors: Daniel A. Beller, Kim M. J. Alards, Francesca Tesser, Ricardo A. Mosna, Federico Toschi, Wolfram Möbius
Optimization of Dose Schedules for Chemotherapy of Early Colon Cancer Determined by High-Performance Computer Simulations
Authors: Chase Cockrell, David E Axelrod
#MathOnco Preprints
A mathematical model of viral oncology as a instigator of immuno-oncology
Authors: Tyler Cassidy, Antony R. Humphries
Quantifying local malignant adaptation in tissue-specific evolutionary trajectories by harnessing cancer's repeatability at the genetic level
Authors: Natsuki Tokutomi, Caroline Moyret-Lalle, Alain PUISIEUX, Sumio Sugano, Pierre Martinez
Density-dependent selection and the limits of relative fitness
Authors: Jason Bertram, Joanna Masel
#MathOnco News
Biology as Information Dynamics
Online Talk: "If biology is the study of self-replicating entities, and we want to understand the role of information, it makes sense to see how information theory is connected to the 'replicator equation' — a simple model of population dynamics for self-replicating entities. The relevant concept of information turns out to be the information of one probability distribution relative to another, also known as the Kullback–Leibler divergence. Using this we can get a new outlook on free energy, see evolution as a learning process, and give a clearer, more general formulation of Fisher's fundamental theorem of natural selection."
#MathOnco - Book of the month
Cellular Automaton Modeling of Biological Pattern Formation: Characterization, Examples, and Analysis
Andreas Deutsch & Sabine Dormann:
"This text explores the use of cellular automata in modeling pattern formation in biological systems. It describes several mathematical modeling approaches utilizing cellular automata that can be used to study the dynamics of interacting cell systems both in simulation and in practice."
Most clicked links of December
Optimizing adaptive cancer therapy: dynamic programming and evolutionary game theory
A mathematical framework for modelling the metastatic spread of cancer
Jobs
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