#MathOnco Issue 53: spatial heterogeneity; pharmacokinetics modeling; measuring subclonal selection; phenotypic switching.
This week in
Mathematical Oncology
Feb. 7, 2019 ~ Issue 53
From the editor
Greetings #MathOnco researchers,
This week's issue has some interesting publications on spatial heterogeneity, pharmacokinetics modeling, measuring subclonal selection, and phenotypic switching.
How is it February already? Anyways, that means you can find January's "most clicked" links at the bottom of this email.
Enjoy,
-Jeffrey West
#MathOnco Publications
Computational Modeling of the Crosstalk Between Macrophage Polarization and Tumor Cell Plasticity in the Tumor Microenvironment
Authors: Xuefei Li, Mohit Kumar Jolly, Jason T. George, Kenneth J. Pienta, Herbert Levine
Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity
Authors: Emelie Berglund, Jonas Maaskola, Niklas Schultz, Stefanie Friedrich, ..., Erik Sonnhammer, Thomas Helleday & Joakim Lundeberg
Variable Cell Line Pharmacokinetics Contribute to Non-Linear Treatment Response in Heterogeneous Cell Populations
Authors: Matthew T. McKenna, Jared A. Weis, Vito Quaranta, Thomas E. Yankeelov
Nonlinear adaptive control of competitive release and chemotherapeutic resistance
Authors: P. K. Newton and Y. Ma
#MathOnco Preprints
On measuring selection in cancer from subclonal mutation frequencies
Authors: Ivana Bozic, Chay Paterson, Bartlomiej Waclaw
Stochastic modeling of phenotypic switching and chemoresistance in cancer cell populations
Authors: Niraj Kumar, Gwendolyn M. Cramer, Seyed Alireza Zamani Dahaj, Bala Sundaram, Jonathan P. Celli, Rahul V. Kulkarni
Evolutionary dynamics of neoantigens in growing tumours
Authors: Eszter Lakatos, Marc J. Williams, Ryan O. Schenck, William C. H. Cross, Jacob Househam, Benjamin Werner, Chandler Gatenbee, Mark Robertson-Tessi, Chris P. Barnes, Alexander R. A. Anderson, Andrea Sottoriva, Trevor A. Graham
#MathOnco News
Papers with Code
Machine Learning: "The mission of Papers With Code is to create a free and open resource with Machine Learning papers, code and evaluation tables. We believe this is best done together with the community and powered by automation. We've already automated the linking of code to papers, and we are now working on automating the extraction of evaluation metrics from papers." -- I wonder if Math Onco could benefit from a similar repository of open math modeling papers & code?
#MathOnco - Book of the month
CSBC/PS-ON Handbook of Mathematical Oncology
A. Anderson, J. Couch, D. Gallahan, N. Moore, K. Swanson, C. Tomlin: The biannual Mathematics of the PS-OC and ICBP workshops were designed to help nurture the developing mathematical oncology community. A direct product of these meetings was a desire to create a shared resource of cancer models and modeling approaches in the form of short and succinct mini-papers with the intention to act as a broader resource that would be enduring for the entire community: a handbook of key methods, concepts, and approaches in Math Oncology.
Most clicked links of January
On the role of tumor heterogeneity for optimal cancer chemotherapy
Paradoxes of tumour complexity: somatic selection, vulnerability by design, or infectious aetiology?
Control Structures of Drug Resistance in Cancer Chemotherapy
Jobs
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