This Week in #MathOnco
This week in
Mathematical Oncology
March 15, 2018 ~ Issue 12
From the editor
Today's issue is as packed full as it is diverse. It contains exciting math oncology models in three types of heterogeneity: genetic, cell signaling, and microenvironmental. Also included are spatio-temporal, statistical mechanics, and stochastic modeling approaches.
Enjoy,
-Jeffrey West
#MathOnco Publications
Cell signaling heterogeneity is modulated by both cell-intrinsic and -extrinsic mechanisms: An integrated approach to understanding targeted therapy
Authors: Eunjung Kim, Jae-Young Kim, Matthew A. Smith, Eric B. Haura, Alexander R. A. Anderson
Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling
Authors: Atsushi Niida, Satoshi Nagayama, Satoru Miyano, Koshi Mimori
Computational approaches and analysis for a spatio-structural-temporal invasive carcinoma model
Authors: Arran Hodgkinson, Mark A. J. Chaplain, Pia Domschke, Dumitru Trucu
Simulating magnetic resonance images based on a model of tumor growth incorporating microenvironment
Authors: Pamela R. Jackson, Andrea Hawkins-Daarud, ..., Kristin R. Swanson
Glioma growth modeling based on the effect of vital nutrients and metabolic products
Authors: Maria Papadogiorgaki, Panagiotis Koliou, Michalis E. Zervakis
#MathOnco Preprints
Cost of resistance: an unreasonably expensive concept
Authors: Thomas Lenormand, Noemie Harmand, Romain Gallet
Cellular cooperation shapes tumor growth: a statistical mechanics mathematical model
Authors: Jeffrey West, Paul K Newton
Stochastic models of cell invasion with fluorescent cell cycle indicators
Authors: Matthew J Simpson, Wang Jin, Sean T Vittadello, ..., Scott McCue
Modeling three-dimensional invasive solid tumor growth in heterogeneous microenvironment under chemotherapy
Authors: Hang Xie, Yang Jiao, Qihui Fan, ..., Liyu Liu
#MathOnco News
Researcher creates 'Instagram' of immune system, blending science, technology.
Carsten Krieg: "Using artificial intelligence and bioinformatics, researchers can create a two-dimensional mapping that can read test results, creating an 'Instagram' of millions of blood cells." A two-dimensional t-stochastic neighbor embedding (tSNE) projection was used for visualization (methods published in Nature Medicine).
#MathOnco Books
Applying Graph Theory
in Ecological Research
Mark R. T. Dale: A broad intro into networks and graphs in ecology: "Graph theory can be applied to ecological questions in many ways, and more insights can be gained by expanding the range of graph theoretical concepts applied to a specific system."
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